[00:00] (0.04s)
it made me recognize one thing that's
[00:02] (2.04s)
very important about your career is how
[00:04] (4.80s)
you interview is the most it's the
[00:08] (8.64s)
highest leverage most important part of
[00:10] (10.84s)
your career like more important than the
[00:12] (12.64s)
impact you even have on the role it's
[00:14] (14.44s)
crazy what you just said is probably one
[00:17] (17.44s)
of the most important lessons that I
[00:19] (19.00s)
learned at Facebook if you were to start
[00:20] (20.84s)
all over again as ic3 knowing what you
[00:23] (23.52s)
know today M what's one thing that You'
[00:26] (26.84s)
change today I'd like to share a
[00:28] (28.96s)
conversation that I had with Zach Wilson
[00:31] (31.72s)
he's an engineer That Grew From Junior
[00:33] (33.84s)
meta to staff engineer at Airbnb by the
[00:37] (37.20s)
age of 26 two of his promotions came
[00:40] (40.20s)
from job hopping which got me curious so
[00:43] (43.28s)
we go into those details we go over his
[00:45] (45.52s)
ratings his compensation and a bunch
[00:48] (48.44s)
more along the way I think you'll like
[00:51] (51.04s)
it since Zach is really transparent with
[00:53] (53.80s)
everything so if this sounds interesting
[00:56] (56.04s)
to you here's the Pod first thing is you
[00:59] (59.56s)
breaking into big Tech can you run me
[01:01] (61.44s)
through that story where were you in
[01:02] (62.96s)
your life how did you get into big Tech
[01:04] (64.80s)
yeah for sure so I started my career at
[01:07] (67.64s)
a bunch of different startups started
[01:09] (69.88s)
off as like a data analyst because I had
[01:11] (71.92s)
dreams of being a math professor for a
[01:13] (73.88s)
while and then I realized like that's
[01:16] (76.52s)
probably not what I want to do because
[01:18] (78.16s)
it's a lot of school to make not very
[01:20] (80.44s)
much money and then I was like okay
[01:22] (82.08s)
probably need to switch and then I was
[01:23] (83.76s)
in started as an analyst I got in at
[01:25] (85.72s)
this company called think big analytics
[01:27] (87.80s)
where they taught me Hadoop but they
[01:29] (89.28s)
taught me Hadoop really a long time ago
[01:31] (91.36s)
it was like 10 years ago now so it was
[01:33] (93.12s)
like right when Hadoop was really early
[01:35] (95.20s)
and uh I owe that experience I feel like
[01:38] (98.80s)
to like the main reason why I got in at
[01:41] (101.28s)
Facebook because that's what they were
[01:42] (102.56s)
looking for was like those kind of Big
[01:44] (104.44s)
Data Technologies and so I jumped around
[01:46] (106.84s)
a lot though because I tried out four
[01:49] (109.08s)
different jobs in two years to like and
[01:51] (111.28s)
then I got the job at Facebook and yeah
[01:53] (113.08s)
it was pretty chaotic because I didn't
[01:54] (114.72s)
know what I wanted to do actually cuz
[01:56] (116.44s)
when I graduated I actually was like I
[01:58] (118.00s)
want to be a mobile engineer but I also
[01:59] (119.48s)
want to be math professor but I also
[02:00] (120.92s)
want to be a data scientist and I was
[02:02] (122.96s)
like I and I just was like okay I need
[02:04] (124.44s)
to do all of these roles at least for a
[02:07] (127.32s)
little bit to understand which one I
[02:08] (128.88s)
want and that's when I landed on data
[02:11] (131.00s)
engineering and I was like all right
[02:12] (132.60s)
this one seems like it fits so were you
[02:14] (134.56s)
a CS major I did the dual major Cs and
[02:17] (137.44s)
applied math dual major yeah I actually
[02:20] (140.12s)
math was first I I finished my math
[02:22] (142.48s)
major first and then got the Cs major
[02:24] (144.52s)
later how was the job market when you
[02:27] (147.48s)
applied for interviews were you able to
[02:29] (149.08s)
get interview yeah I think right now is
[02:31] (151.40s)
a challenging time but I definitely
[02:33] (153.32s)
found that like when I first graduated I
[02:35] (155.40s)
interviewed bunch of places government
[02:37] (157.60s)
jobs cuz like where I grew up there's
[02:38] (158.88s)
tons of like government jobs on a
[02:40] (160.28s)
military base like interviewed there
[02:42] (162.36s)
interviewed in Salt Lake and all across
[02:44] (164.72s)
the valley I probably got four five
[02:46] (166.08s)
different interviews though like with no
[02:47] (167.60s)
experience and just like the only
[02:49] (169.28s)
experience I had was I was a math tutor
[02:51] (171.12s)
that was all I had so yeah I feel very
[02:53] (173.32s)
lucky that was like my getting into the
[02:56] (176.08s)
industry experience for sure these were
[02:57] (177.68s)
CS jobs yeah uh CS an analyst like it
[03:00] (180.92s)
was like those two I was trying to
[03:02] (182.56s)
decide between the two because yeah the
[03:04] (184.48s)
government job was going to be a CS role
[03:06] (186.52s)
I actually ended up not taking that role
[03:08] (188.40s)
though yeah okay so how did you find
[03:10] (190.40s)
your way into Facebook then yeah so it
[03:13] (193.44s)
was wild because so I did one year in
[03:15] (195.48s)
Utah and then I got like very frustrated
[03:17] (197.60s)
with Utah then I moved to DC because I
[03:20] (200.16s)
was like I'm just want to leave my home
[03:22] (202.56s)
state want to try something new I was in
[03:24] (204.24s)
DC for six seven months and then that's
[03:26] (206.40s)
when a Facebook recruiter reached out to
[03:27] (207.84s)
me and they were like hey you should
[03:29] (209.20s)
interview and I'm like this is wild cuz
[03:31] (211.76s)
back in Utah I did interview at Google
[03:33] (213.68s)
twice actually for Mobile and got
[03:36] (216.48s)
rejected both times and so I was like it
[03:40] (220.20s)
but I applied to Google and I it felt
[03:42] (222.16s)
very magical when it was like the
[03:43] (223.96s)
Facebook recruiter reached out to me I
[03:45] (225.48s)
was like I felt like Facebook was
[03:46] (226.64s)
applying to me almost I was like okay
[03:48] (228.36s)
yeah sure I'll give an interview was
[03:50] (230.00s)
that through Linkedin or yeah LinkedIn
[03:51] (231.56s)
for sure linkedin's been so critical for
[03:53] (233.88s)
my whole career since that job at think
[03:55] (235.92s)
big like in 2015 at the time you didn't
[03:58] (238.72s)
post on LinkedIn no definitely not
[04:00] (240.56s)
definitely not like I do now okay so
[04:02] (242.48s)
they inbounded and then you interviewed
[04:04] (244.52s)
with them MH and you got the role and
[04:06] (246.64s)
was the interview explicitly for data
[04:08] (248.24s)
engineer yes I see I see okay so then
[04:11] (251.28s)
you got the role do were you applying to
[04:13] (253.20s)
other places at the same time no
[04:15] (255.04s)
actually I was pretty happy with my role
[04:17] (257.16s)
in DC there was a lot of trajectory
[04:19] (259.24s)
there it was interesting cuz when I got
[04:20] (260.76s)
the offer from Facebook my role in DC
[04:22] (262.76s)
countered with more money actually and I
[04:25] (265.64s)
was like whoa I was not expecting them
[04:27] (267.40s)
to they were like here's 100% raise and
[04:29] (269.48s)
I but the thing was I didn't take it
[04:31] (271.68s)
because two months before I asked them
[04:34] (274.12s)
for a 20% raise and they said they
[04:35] (275.68s)
didn't have the budget and I was like
[04:37] (277.52s)
okay if y'all only have the budget when
[04:39] (279.72s)
I have my foot out the door I know that
[04:42] (282.20s)
career growth here is going to be
[04:43] (283.80s)
painful it's going to be super painful
[04:46] (286.08s)
even though it's more money even though
[04:47] (287.52s)
it's a cheaper place to live I'm going
[04:49] (289.28s)
to California for less money and a more
[04:51] (291.68s)
expensive place to live because I
[04:53] (293.04s)
believe in the future oh so actually
[04:55] (295.36s)
Facebook paid you less it was a raise
[04:58] (298.12s)
based off of what I was making but the
[04:59] (299.84s)
counter offer that I got from my company
[05:02] (302.28s)
in DC was more money I see I see it was
[05:05] (305.00s)
like 180 was what Facebook offered me
[05:07] (307.16s)
and then they countered with 200 one
[05:09] (309.44s)
think okay okay sounds good so then you
[05:11] (311.32s)
got into Facebook as a data engineer how
[05:14] (314.76s)
was the moving to Silicon Valley and I
[05:18] (318.12s)
loved it like I there was a couple other
[05:19] (319.96s)
motivating factors for me to come back
[05:21] (321.48s)
to California because I grew up in Utah
[05:23] (323.12s)
and like being a DC being far away from
[05:25] (325.48s)
family all that stuff was like also
[05:27] (327.40s)
isolating and being in California is
[05:29] (329.20s)
really nice cuz I'm still pretty close
[05:30] (330.96s)
to Utah I can drive home any day I want
[05:33] (333.92s)
in one day if I want to do that but
[05:35] (335.88s)
getting into Silicon Valley was really
[05:37] (337.76s)
great it was really wonderful I really
[05:39] (339.64s)
felt especially those like first couple
[05:41] (341.12s)
days like those boot camp tasks that
[05:43] (343.16s)
they give you and they're like go and do
[05:45] (345.72s)
this scavenger hunt right I don't know
[05:47] (347.96s)
it always like my that first like month
[05:50] (350.56s)
at Facebook didn't even feel like I was
[05:52] (352.44s)
like working a job it felt like I was in
[05:54] (354.04s)
like Disneyland it felt like I was this
[05:55] (355.64s)
is a job like I'm going to work here it
[05:57] (357.64s)
didn't really it it it was very good at
[06:00] (360.00s)
getting me to adopt move fast and break
[06:02] (362.28s)
things this is your company be bold all
[06:05] (365.08s)
those like kind of tenants of Facebook
[06:07] (367.20s)
that like it because it was such a great
[06:09] (369.56s)
onboarding experience I was like wow
[06:11] (371.60s)
this company is something else I love
[06:13] (373.72s)
boot camp it felt like an extension of
[06:17] (377.16s)
college or something because you're
[06:18] (378.04s)
going to all these classes you're just
[06:20] (380.48s)
learning you're not being held
[06:22] (382.44s)
accountable for any deadlines or
[06:23] (383.80s)
anything yet so that was really great
[06:26] (386.56s)
okay so you come into boot camp how did
[06:29] (389.16s)
you pick the team that you were in great
[06:31] (391.48s)
question so I had three choices I was
[06:33] (393.72s)
either going to join ads I was going to
[06:35] (395.28s)
join growth or I was going to join
[06:37] (397.20s)
Community Support those are the three
[06:39] (399.12s)
that they had me interview with and
[06:42] (402.08s)
essentially for me it was like which one
[06:43] (403.52s)
was different with ads they were like if
[06:45] (405.64s)
you come in here you're going to provide
[06:47] (407.44s)
data that's going to make Facebook
[06:48] (408.60s)
millions and I'm like wow interesting
[06:50] (410.16s)
impact and then for Community Support
[06:51] (411.80s)
they were like if you come in here you
[06:53] (413.44s)
can help prevent a lot of bad stuff on
[06:54] (414.84s)
Facebook and then growth they're like if
[06:58] (418.68s)
you join us you'll have a lot of fun and
[07:01] (421.84s)
I was like sold and I ended up joining
[07:05] (425.28s)
growth I think it was a combination of
[07:06] (426.92s)
that and then the manager was more of
[07:08] (428.80s)
this entrepreneurial stupy guy his name
[07:11] (431.24s)
is jender he's going to make a couple
[07:12] (432.88s)
other cameo appearances in the rest of
[07:14] (434.36s)
this podcast but he was great guy really
[07:17] (437.20s)
great guy he's still one of my best
[07:18] (438.36s)
friends to this day and that's why I
[07:20] (440.64s)
ended up picking core growth and
[07:22] (442.04s)
notifications specifically when you
[07:24] (444.24s)
joined did you know much about the
[07:26] (446.48s)
career ladder or were you thinking about
[07:28] (448.16s)
it no there was so many things I didn't
[07:30] (450.12s)
know for example like I actually didn't
[07:32] (452.32s)
even understand like L3 L4 L5 I I didn't
[07:36] (456.44s)
understand I didn't understand that I
[07:37] (457.80s)
was getting hired in at L3 because one
[07:40] (460.00s)
of the things that like really was
[07:42] (462.36s)
disconcerting to me when I got in at
[07:44] (464.32s)
Facebook was like I had two years of
[07:46] (466.28s)
experience I'd been working in startups
[07:48] (468.72s)
and doing big data pipelines for two
[07:50] (470.32s)
years and then there's these kids from
[07:52] (472.04s)
Stanford who get hired and they get paid
[07:54] (474.40s)
the same as me with zero years of
[07:56] (476.08s)
experience and I was like this is unfair
[07:58] (478.92s)
and I re that was one of the things I
[08:00] (480.44s)
recognized pretty early on in my time at
[08:02] (482.36s)
Facebook which also I think spoiled my
[08:05] (485.44s)
time at Facebook is because I recognized
[08:07] (487.84s)
hey like I got hired at the wrong level
[08:10] (490.36s)
so I need to bust my ass to get to the
[08:12] (492.32s)
next level which I did it was like like
[08:15] (495.12s)
seven months from I was only L3 for a
[08:17] (497.24s)
very short amount of time but I think
[08:19] (499.04s)
that was something that definitely
[08:20] (500.80s)
bothered me as I I recognized it made me
[08:23] (503.68s)
recognize one thing that's very
[08:25] (505.44s)
important about your career is how you
[08:28] (508.24s)
interview is the most it's the highest
[08:32] (512.24s)
leverage most important part of your
[08:34] (514.28s)
career like more important than the
[08:35] (515.88s)
impact you even have on the role it's
[08:37] (517.68s)
crazy like yeah one of the things that
[08:39] (519.92s)
interests me most in your story is you
[08:44] (524.00s)
were able to successfully interview into
[08:47] (527.00s)
promotions multiple times and I think a
[08:50] (530.04s)
lot of people wonder how you do that I'm
[08:52] (532.48s)
myself I'm also curious what were those
[08:54] (534.44s)
conversations like when you having the
[08:55] (535.88s)
interviews how did you get placed in the
[08:57] (537.88s)
staff how did you get placed in the
[08:59] (539.00s)
senior but yeah we'll go into that later
[09:00] (540.80s)
in the podcast so you got promoted in
[09:03] (543.12s)
one half so what how did that work was
[09:05] (545.96s)
that expected or I recognized pretty
[09:08] (548.84s)
early on that I was going to succeed at
[09:11] (551.16s)
Facebook just because of I like how
[09:13] (553.12s)
everything was tasked out and how there
[09:14] (554.84s)
was just I had a lot of energy and I
[09:16] (556.60s)
could tell that I was shipping a lot of
[09:17] (557.80s)
code and I was moving a lot of things
[09:19] (559.36s)
and I picked up notifications very
[09:21] (561.12s)
quickly so like they had this like
[09:23] (563.64s)
waterfall framework for notifications
[09:25] (565.92s)
which is like essentially tracking like
[09:28] (568.12s)
conversion rates or clicked rates or
[09:30] (570.04s)
delivery rates all those different like
[09:32] (572.40s)
funnel metrics that you can do they had
[09:34] (574.68s)
this whole framework for that but the
[09:35] (575.96s)
framework sucked and one of the reasons
[09:37] (577.84s)
why I got that promotion was I was also
[09:41] (581.12s)
like let's fix the framework but one of
[09:43] (583.16s)
the things about that was like that was
[09:44] (584.64s)
actually like xhp work that was not like
[09:47] (587.16s)
SQL python work at all and like when my
[09:49] (589.48s)
manager saw that I I was like I'm just
[09:51] (591.28s)
going to fix it just going to go and
[09:52] (592.60s)
learn xhp and react and fix it and he
[09:55] (595.08s)
was like wow this guy knows how to solve
[09:57] (597.24s)
a problem like even when it's not in
[09:59] (599.76s)
data engineering it's it's a full stack
[10:01] (601.56s)
problem and that was something I
[10:03] (603.36s)
demonstrated really early on to my
[10:04] (604.76s)
manager was that like I'm not going to
[10:06] (606.40s)
let a skill set or think that's not my
[10:08] (608.72s)
problem it's I'm going to learn and
[10:10] (610.88s)
figure out like what needs to be done
[10:12] (612.48s)
and solve the problem and yeah for sure
[10:14] (614.56s)
it was did anyone tell you to to do that
[10:17] (617.20s)
or no not really I think that's the
[10:18] (618.96s)
other part of why I grew really close
[10:21] (621.16s)
with this manager as well is because I
[10:22] (622.84s)
recognized like where the impact is
[10:24] (624.68s)
right not just being like okay I'm going
[10:25] (625.96s)
to finish my tasks and be done with it
[10:27] (627.96s)
that's how you get meets all finish your
[10:29] (629.36s)
tasks do them as they were assigned
[10:30] (630.72s)
especially at L3 if you do exactly what
[10:32] (632.24s)
your task says you'll get meets all and
[10:34] (634.04s)
it's going to be great but if you want
[10:35] (635.60s)
to do more which I was very hungry to do
[10:38] (638.04s)
more especially when I realized that I
[10:39] (639.72s)
was hired in at the wrong level I was
[10:41] (641.92s)
like okay I have to just get out of this
[10:43] (643.80s)
situation as quickly as possible so
[10:45] (645.96s)
that's why I also did those things
[10:47] (647.48s)
because I wanted to demonstrate to them
[10:49] (649.08s)
like I have experience I'm a skilled
[10:51] (651.24s)
person and yeah for sure did the promo
[10:54] (654.08s)
just happen or were you aware of it and
[10:57] (657.08s)
expecting that to come at any point not
[10:59] (659.32s)
the promo did just happen like that
[11:01] (661.04s)
first promo that had no idea your
[11:02] (662.88s)
manager was yeah because a couple things
[11:04] (664.80s)
about it was like I actually got it
[11:06] (666.36s)
wasn't even a full half because I got
[11:08] (668.16s)
hired in at the end of July so I missed
[11:11] (671.20s)
a month of that half as well so it was
[11:13] (673.36s)
five months so but like definitely the
[11:16] (676.64s)
that that promo just was like I think
[11:18] (678.72s)
they recognized that I was hired at the
[11:20] (680.72s)
wrong level and that's why they gave it
[11:22] (682.56s)
to me it they weren't going to make me
[11:24] (684.08s)
like do all the steps of getting there
[11:27] (687.12s)
or whatever yeah yeah usually when
[11:29] (689.40s)
motions happen in just a half yeah that
[11:31] (691.96s)
means that was mis leveling and that's
[11:34] (694.56s)
an opportunity if you just joined
[11:36] (696.32s)
Facebook and you all of a sudden were
[11:39] (699.04s)
performing as ic5 they'll just promote
[11:41] (701.72s)
you quickly because they take that as it
[11:44] (704.52s)
was a Miss on the hiring and I think
[11:46] (706.48s)
that's one of the things that is really
[11:48] (708.08s)
cool about working there and about these
[11:50] (710.76s)
tech companies is that they will do that
[11:52] (712.48s)
because it's not I don't know at least
[11:54] (714.08s)
like growing up in Utah and everything
[11:56] (716.00s)
it's not based on impact it's based on
[11:57] (717.28s)
tenure right it's based on okay been
[11:59] (719.40s)
here three years okay you're a senior
[12:00] (720.96s)
engineer now and it's based on just like
[12:03] (723.12s)
amount of time in the role and that was
[12:06] (726.28s)
probably one of the most beautiful
[12:07] (727.84s)
things that shifted my mentality when I
[12:11] (731.00s)
moved to the Bay Area because when I was
[12:13] (733.72s)
in Utah I thought that the very most
[12:16] (736.20s)
money that I was going to make in my
[12:17] (737.76s)
career as a software engineer was 200k
[12:20] (740.20s)
200k was going to be and that was like
[12:21] (741.80s)
15 years deep that's why that was me
[12:24] (744.04s)
imagining myself at 35 and then when I
[12:26] (746.60s)
get in at Facebook and I'm like no
[12:27] (747.92s)
they're like okay no we're going to give
[12:28] (748.72s)
you 200k now and there's a freaking
[12:31] (751.04s)
trajectory to go to a million if you
[12:33] (753.12s)
want and it really showed me that
[12:35] (755.40s)
there's so much more to this life and so
[12:37] (757.20s)
much more to like engineering than just
[12:38] (758.80s)
I'm working at a company I'm closing
[12:40] (760.60s)
Jura tickets but it's if you actually
[12:42] (762.24s)
start to care about the impact of the
[12:43] (763.72s)
business like it they reward you right
[12:46] (766.08s)
they give back it's awesome because you
[12:48] (768.92s)
can create so much value too you
[12:50] (770.72s)
actually make more than you cost it's
[12:52] (772.72s)
easy for them to Warrant paying you that
[12:54] (774.88s)
much oh yeah for sure it's okay it's
[12:56] (776.28s)
like you save us 10 mil we'll give you a
[12:57] (777.72s)
little bit more money sure yeah
[12:59] (779.52s)
sometimes when people save 10 mil I'm
[13:01] (781.28s)
like just give me a little 1% I'll take
[13:05] (785.00s)
a little bit yeah yeah yeah okay so you
[13:07] (787.80s)
got promoted from 3: to 4 yeah because
[13:10] (790.32s)
you had insane initiative sounds like
[13:13] (793.00s)
you were working a lot of hours how many
[13:14] (794.80s)
hours a week would you say uh so after
[13:16] (796.28s)
boot camp I ramped up I would say
[13:18] (798.36s)
probably 50 to 60 very common I think
[13:21] (801.40s)
for me where it would be like I would
[13:23] (803.28s)
get in at 9 9:30 and then I would stay
[13:27] (807.24s)
till 8 8 at night cuz i' do breakfast
[13:29] (809.60s)
lunch and dinner TR all meals cuz you
[13:31] (811.52s)
know I'm still this way I feel like this
[13:33] (813.00s)
is one of the things where Facebook
[13:34] (814.44s)
ruined me a little bit is that they're
[13:35] (815.80s)
like we're just going to feed you all
[13:37] (817.12s)
your meals and then I'm like now I'm 30
[13:39] (819.12s)
and I'm like I still don't know how to
[13:40] (820.48s)
cook and I'm like this is a problem I'm
[13:42] (822.36s)
like it's a basic life skill that I was
[13:44] (824.44s)
able to avoid learning and I'm like this
[13:46] (826.40s)
is a rough situation but definitely I
[13:48] (828.40s)
would say yeah around that got it you
[13:50] (830.32s)
know so then after you got pred to four
[13:52] (832.80s)
then well were you hungry for five oh
[13:54] (834.64s)
yeah when I got four I was like I want
[13:56] (836.48s)
five in a year and I was like I'm going
[13:57] (837.88s)
to work for it I'm going to crush it and
[14:00] (840.08s)
yeah and it didn't happen so what was
[14:02] (842.84s)
your plan did you talk to your manager
[14:04] (844.84s)
yeah I did I talked with my manager so a
[14:06] (846.92s)
couple things happened that I and jender
[14:09] (849.48s)
like that when he was my manager I
[14:12] (852.48s)
actually was pretty confident that it
[14:13] (853.96s)
was going to happen problem was that
[14:16] (856.00s)
next summer jender left and then there
[14:18] (858.24s)
was a period of time where we all just
[14:19] (859.92s)
reported to the director right and I
[14:22] (862.44s)
didn't really have a great relationship
[14:23] (863.88s)
with him and then eventually we got a
[14:26] (866.04s)
new guy in right and it's funny cuz that
[14:28] (868.76s)
guy came from Netflix which is so
[14:30] (870.80s)
bizarre ultimately because then I left
[14:32] (872.32s)
to Netflix I'm like Netflix and Facebook
[14:34] (874.24s)
are all it's all the same people dude
[14:36] (876.52s)
but I had a plan and I actually felt
[14:38] (878.08s)
like I actually did deliver on the value
[14:41] (881.08s)
that was necessary to get to senior but
[14:43] (883.52s)
and my view on it was the fact that I
[14:45] (885.68s)
had three managers that year I had
[14:47] (887.12s)
jender I had Nick and I had sat and no
[14:49] (889.88s)
one really had the context right because
[14:51] (891.76s)
I'm like how many times do I have to
[14:53] (893.28s)
tell my manager what I did why do I have
[14:55] (895.08s)
to do this again and again and and I
[14:56] (896.88s)
think that was ultimately the thing that
[14:58] (898.48s)
kind of disrup rupted the plan but it
[15:00] (900.44s)
also goes to show that having a good
[15:01] (901.92s)
manager who trusts you takes time and
[15:04] (904.96s)
you have to build that up with them you
[15:06] (906.68s)
have to prove that to them right and
[15:09] (909.08s)
they're not like the good managers will
[15:10] (910.76s)
trust like implicitly and then they will
[15:12] (912.88s)
only remove trust when you give them a
[15:14] (914.80s)
reason to not trust you but some
[15:16] (916.64s)
managers are like no you got to prove it
[15:18] (918.28s)
right that's where it's like different
[15:19] (919.56s)
it depends on who your manager is so you
[15:21] (921.56s)
had jender for a half or how he was my
[15:24] (924.60s)
manager for a little bit over a year but
[15:26] (926.96s)
so after you got promoted yeah that
[15:29] (929.00s)
first half did he do your PSC that half
[15:31] (931.56s)
yeah for the promotion yeah for the for
[15:33] (933.68s)
just yeah he did the first promotion but
[15:35] (935.48s)
after that no no not the because he left
[15:37] (937.24s)
after that okay yeah half as an E4 yeah
[15:41] (941.20s)
and then you got a new manager yeah and
[15:44] (944.04s)
that half though how's your PSC was it I
[15:46] (946.08s)
got greatly exceeds okay you got greatly
[15:48] (948.16s)
exceeds as an E4 in your first half okay
[15:51] (951.20s)
yeah that's signal that you're doing
[15:53] (953.36s)
really well yeah what prevented the
[15:56] (956.00s)
promotion the next time great question I
[15:57] (957.96s)
think what happened the next half was it
[15:59] (959.80s)
was greatly again right like got and
[16:02] (962.92s)
what they were saying was that like I
[16:05] (965.16s)
was not operating as a senior engineer
[16:07] (967.12s)
because I was still focusing too much on
[16:10] (970.32s)
problems that I like that they were like
[16:11] (971.96s)
you're taking on too much work and that
[16:13] (973.60s)
they're like you are delivering as an E5
[16:16] (976.72s)
but you like they they their belief was
[16:19] (979.24s)
that I would not sustainably deliver
[16:21] (981.40s)
like that that was and I'm like which
[16:23] (983.76s)
was something that like pissed me off a
[16:25] (985.92s)
lot definitely a thing that comes up
[16:28] (988.12s)
it's a bummer because you would think
[16:30] (990.96s)
that the harder you work the more you
[16:32] (992.72s)
would get rewarded with promotions but
[16:35] (995.12s)
one of the things they're looking for is
[16:36] (996.72s)
that your promotion's sustainable and
[16:40] (1000.72s)
it's funny because if you're working a
[16:42] (1002.84s)
lot to get those results people might
[16:45] (1005.60s)
wonder oh can he keep this up yeah what
[16:48] (1008.64s)
if he starts working normal hours MH is
[16:51] (1011.36s)
he not going to meet expectations 100%
[16:53] (1013.88s)
that's that was right there what you
[16:56] (1016.76s)
just said is probably what of the most
[16:59] (1019.48s)
important lessons that I learned at
[17:00] (1020.84s)
Facebook which is that hours work does
[17:03] (1023.04s)
not necessarily influence like your
[17:07] (1027.36s)
promotion ability there is a point where
[17:10] (1030.12s)
it's like hours work helps with
[17:11] (1031.56s)
addressing like skill gaps if you have a
[17:13] (1033.72s)
gap then you can cover the Gap by
[17:16] (1036.40s)
working more but that does not
[17:18] (1038.24s)
necessarily instill confidence and
[17:19] (1039.96s)
Leadership that you are promotion worthy
[17:22] (1042.68s)
right for sure definitely because
[17:24] (1044.76s)
they're looking for behaviors they're
[17:27] (1047.80s)
looking for someone that can take on
[17:31] (1051.16s)
more leadership not necessarily just
[17:33] (1053.16s)
work additional hours to have the impact
[17:35] (1055.88s)
so get it but also at the same time it
[17:38] (1058.36s)
can be you know pretty something that
[17:41] (1061.20s)
can make a hard worker very salty yeah
[17:44] (1064.20s)
yeah and I think for me what ended up
[17:46] (1066.04s)
happening was that next like going into
[17:47] (1067.92s)
the next year because those promos
[17:49] (1069.64s)
usually happen in like March or whatever
[17:51] (1071.40s)
and I after learning I'm like I'm not
[17:53] (1073.56s)
getting promoted I was like time to go
[17:55] (1075.12s)
and take the story because this is one
[17:56] (1076.92s)
of the things I think is super important
[17:58] (1078.24s)
when you think about interviewing is I
[18:00] (1080.68s)
knew that I had a story that would get
[18:04] (1084.44s)
me a senior role because guess what
[18:08] (1088.00s)
Facebook told me that they said I was
[18:09] (1089.80s)
greatly exceeding expectations and guess
[18:11] (1091.84s)
what know the best part about
[18:12] (1092.88s)
interviewing is they don't know how many
[18:14] (1094.28s)
hours I worked they just know what I did
[18:16] (1096.72s)
right they don't know how many hours I
[18:18] (1098.16s)
work they like in the interview they get
[18:20] (1100.04s)
a different vantage point of what your
[18:22] (1102.36s)
impact was and what you did and they
[18:24] (1104.48s)
don't get as much of the negative data
[18:26] (1106.32s)
right they don't get as much of that and
[18:27] (1107.72s)
so for me recognized that I was like I
[18:30] (1110.64s)
know I can go to any other big tech
[18:32] (1112.08s)
company and be a senior engineer I
[18:33] (1113.68s)
already knew that especially like after
[18:35] (1115.72s)
all the optimizations I made the
[18:37] (1117.40s)
notification machine learning algorithm
[18:39] (1119.16s)
all that stuff there was like some very
[18:40] (1120.56s)
technical nitty-gritty things that I did
[18:42] (1122.44s)
that were really impactful that I was
[18:44] (1124.52s)
like I know if I just talk about that in
[18:46] (1126.44s)
the detail that I know people are going
[18:48] (1128.56s)
to give me what I want so to be clear
[18:50] (1130.48s)
you got two great League seeds in a row
[18:53] (1133.08s)
as ic4 yeah which is midlevel and then
[18:55] (1135.96s)
you didn't get promoted so instantly you
[18:59] (1139.16s)
realized okay because I'm greatly
[19:01] (1141.52s)
exceeding I can get ic5 somewhere else
[19:04] (1144.44s)
yeah 100% And also the thing that
[19:06] (1146.36s)
blocked your promotion it's not going to
[19:08] (1148.40s)
be a blocker somewhere else yep yeah for
[19:10] (1150.24s)
sure okay so then how did you sell that
[19:12] (1152.56s)
as a ic5 to the next place cuz when I
[19:16] (1156.16s)
think of what qualifies for an ic5 if
[19:19] (1159.48s)
you're interviewing they'll say yeah
[19:21] (1161.12s)
certain number of years of experience
[19:23] (1163.12s)
and various other things they might also
[19:25] (1165.00s)
want to know what level you are at meta
[19:26] (1166.80s)
so how did you get Netflix level as an
[19:29] (1169.56s)
ic5 when you're midlevel not that many
[19:33] (1173.12s)
years of experience I feel like the
[19:34] (1174.60s)
Netflix one was there was also one more
[19:36] (1176.84s)
element of luck here and that element of
[19:39] (1179.08s)
luck is that the hiring manager was
[19:41] (1181.28s)
jender so I'm like all right jender
[19:43] (1183.64s)
you've already seen my work you trust me
[19:45] (1185.48s)
what's up and so that helped a lot like
[19:47] (1187.68s)
having the right connections that's why
[19:49] (1189.20s)
building a network is important that's
[19:50] (1190.84s)
why I'm all about brand personal brand
[19:52] (1192.76s)
and I think a lot of people conflate
[19:54] (1194.44s)
personal branding with making content on
[19:56] (1196.28s)
LinkedIn or like putting your voice or a
[19:58] (1198.96s)
blog post or making YouTube videos or
[20:01] (1201.16s)
whatever but there's also like this idea
[20:02] (1202.80s)
of internal brand which is like how are
[20:05] (1205.20s)
you known in the company how are you
[20:06] (1206.76s)
known by the people you work with and
[20:08] (1208.40s)
it's if you are if you're able to build
[20:10] (1210.00s)
a strong internal brand that's what it
[20:12] (1212.12s)
did it's because I worked really hard
[20:13] (1213.60s)
with jender and he saw what I was
[20:15] (1215.32s)
capable of and capable of doing because
[20:17] (1217.40s)
for me there was one other problem that
[20:19] (1219.48s)
I had with Facebook actually which was I
[20:22] (1222.88s)
and there was one other conversation
[20:24] (1224.64s)
that I had that like really frustrated
[20:26] (1226.56s)
me was I also wanted to not be a data
[20:30] (1230.68s)
engineer anymore right cuz I was like
[20:33] (1233.32s)
I'm done because I've been shipping so
[20:34] (1234.68s)
much like react and PHP and hack code
[20:37] (1237.68s)
and all this stuff and I even was
[20:39] (1239.28s)
talking to my managers like dude like
[20:40] (1240.88s)
compared to all the other data Engineers
[20:42] (1242.92s)
on this team I am writing I'm I because
[20:45] (1245.68s)
I even gave him the number I'm like of
[20:47] (1247.56s)
so I was on a team of 15 data engineers
[20:49] (1249.28s)
and I'm like I'm writing 90% of the
[20:52] (1252.04s)
JavaScript code from our team me just me
[20:55] (1255.48s)
and so it's I am not doing the same work
[20:58] (1258.24s)
that like other data Engineers are doing
[21:00] (1260.04s)
so I feel like I should not be a data
[21:01] (1261.44s)
engineer I should be a software engineer
[21:02] (1262.88s)
and software engineers get more Equity
[21:04] (1264.60s)
because because data Engineers are
[21:05] (1265.60s)
technically not on the E Track like
[21:07] (1267.40s)
their IC track they're like and so they
[21:09] (1269.28s)
get like it's like 30 40% less equity
[21:12] (1272.12s)
which is I was like that was the other
[21:13] (1273.20s)
thing I was like unfair I'm a software
[21:15] (1275.08s)
engineer I'm a real engineer and so
[21:17] (1277.04s)
there was one more conversation I had
[21:18] (1278.52s)
there that like really set me off that
[21:20] (1280.08s)
made me like really not want to work at
[21:22] (1282.40s)
Facebook anymore which was like so one
[21:24] (1284.28s)
was like I really wanted to be like L5
[21:26] (1286.64s)
and the other one was I wanted to switch
[21:28] (1288.24s)
the song software engineer and when I
[21:29] (1289.76s)
talked with my manager about switching
[21:31] (1291.28s)
software engineer they were like hey we
[21:33] (1293.04s)
can switch you to software engineer
[21:34] (1294.16s)
we're gonna have to down level you
[21:35] (1295.20s)
though and I'm like I'm not going to be
[21:37] (1297.04s)
an L3 software engineer that is absurd
[21:39] (1299.96s)
that is patently absurd for me to do
[21:42] (1302.32s)
that that is an absurd statement that
[21:44] (1304.72s)
you even said that came out of your
[21:46] (1306.12s)
mouth right there why they were like
[21:47] (1307.96s)
you're not going to have all the skills
[21:49] (1309.28s)
necessary for it and again that was the
[21:50] (1310.84s)
thing where I point what about the stuff
[21:52] (1312.12s)
I'm shipping B's code over here see this
[21:54] (1314.24s)
stuff I've already built and that stuff
[21:55] (1315.80s)
didn't matter they they just looked at
[21:57] (1317.24s)
title and comes back to having the right
[22:01] (1321.36s)
manager matters so much it matters so
[22:04] (1324.04s)
much because then they're actually able
[22:05] (1325.72s)
to listen to your career goals and
[22:07] (1327.12s)
actually take into account all of those
[22:08] (1328.72s)
things right they're not just your data
[22:09] (1329.92s)
engineer so and for a while that was
[22:12] (1332.04s)
actually like standard practice at
[22:13] (1333.28s)
Facebook if you wanted to go from data
[22:14] (1334.80s)
engineer to software engineer they down
[22:16] (1336.24s)
leled you but not the other way around
[22:18] (1338.00s)
which I always thought was interesting
[22:19] (1339.40s)
I'm like okay so there's like this
[22:21] (1341.00s)
software engineer Supremacy at Facebook
[22:22] (1342.96s)
or something like that where they're
[22:23] (1343.92s)
like yeah software Engineers are here
[22:25] (1345.36s)
data Engineers are here it's yeah for
[22:27] (1347.44s)
sure that's where that was the other
[22:29] (1349.00s)
thing I recognized was I wanted to work
[22:32] (1352.44s)
on data stuff that wasn't just SQL
[22:36] (1356.16s)
because now I learned more and like the
[22:38] (1358.08s)
field has changed data engineering has
[22:39] (1359.92s)
changed and technically the role I had
[22:42] (1362.20s)
at Facebook was not data engineering it
[22:44] (1364.72s)
would not be titled that today today it
[22:47] (1367.20s)
would be titled analytics engineering
[22:49] (1369.24s)
which a different title right and that's
[22:51] (1371.12s)
like more sequal experimentation product
[22:54] (1374.32s)
analytics focused whereas data
[22:56] (1376.04s)
engineering is more about like big data
[22:57] (1377.76s)
pipelines and like spark and so more
[23:00] (1380.72s)
Technical and not not as much analytical
[23:02] (1382.72s)
and and that I was drawn more to that
[23:04] (1384.76s)
kind of stuff as well so do you think if
[23:07] (1387.00s)
you had a better manager that you
[23:09] (1389.24s)
wouldn't have been downlevel oh no I
[23:11] (1391.60s)
definitely not if I would have had a
[23:12] (1392.72s)
more supportive manager there that I
[23:14] (1394.20s)
would have been able to tr because guess
[23:15] (1395.92s)
what I have a friend who works at
[23:17] (1397.96s)
Facebook his name is also Ryan and he
[23:20] (1400.20s)
still works at Facebook and guess what
[23:22] (1402.20s)
his manager was supportive and he
[23:24] (1404.04s)
transitioned this week and he I've
[23:26] (1406.28s)
always I always look at his life and I'm
[23:27] (1407.92s)
like your life is the life I would have
[23:30] (1410.20s)
had if I didn't have a bad manager and
[23:32] (1412.60s)
he's still there he's been at meta like
[23:33] (1413.96s)
nine years now he's been there for a
[23:35] (1415.48s)
long time he's doing all all this crazy
[23:37] (1417.16s)
stuff like scuba and stuff like that
[23:39] (1419.00s)
good stuff but like for sure definitely
[23:41] (1421.32s)
that is definitely uh something that I
[23:43] (1423.48s)
believe especially because when I was
[23:46] (1426.40s)
talking with jender at Netflix he was
[23:48] (1428.12s)
like hey I don't know if I can hire you
[23:50] (1430.76s)
in as a senior software engineer because
[23:53] (1433.92s)
you don't have very much experience in
[23:55] (1435.64s)
software engineering but he was like I
[23:57] (1437.48s)
can hire you in as a senior data
[23:59] (1439.36s)
engineer and then I can get you to
[24:01] (1441.44s)
transition to software engineer in six
[24:03] (1443.88s)
to six to 12 months and I was like
[24:06] (1446.20s)
perfect perfect that sounds great and so
[24:07] (1447.92s)
that's what ended up happening I got
[24:09] (1449.12s)
hired in at Netflix was there for six
[24:10] (1450.92s)
months and then the rest of my time at
[24:12] (1452.72s)
Netflix I was senior software engineer
[24:15] (1455.00s)
and I I worked didn't really do as much
[24:17] (1457.36s)
data pipeline work got it okay so going
[24:20] (1460.80s)
back to your transition from Facebook to
[24:22] (1462.80s)
Netflix yeah it was a connection with
[24:25] (1465.96s)
your old manager who gave gave you such
[24:29] (1469.56s)
a strong recommendation that you were
[24:32] (1472.76s)
put into a senior pipeline yep and
[24:35] (1475.40s)
Netflix only hired seniors okay so there
[24:37] (1477.72s)
wasn't any it was senior or you're not
[24:39] (1479.68s)
in it's different now they added levels
[24:41] (1481.52s)
like two years ago but yeah back in 2018
[24:43] (1483.80s)
there was no staff either were you
[24:45] (1485.24s)
working directly on his team or yeah he
[24:47] (1487.48s)
was my direct manager yeah was his
[24:49] (1489.32s)
recommendation especially powerful cuz
[24:52] (1492.00s)
like I can recommend people The Meta but
[24:54] (1494.12s)
it's not especially powerful or anything
[24:57] (1497.44s)
the reason for that is because meta has
[24:59] (1499.60s)
more standardized interview processes
[25:01] (1501.64s)
that's not how it is at Netflix at
[25:02] (1502.96s)
Netflix it's freedom and responsibility
[25:05] (1505.44s)
and they give managers a lot of power at
[25:07] (1507.24s)
Netflix right they also give managers a
[25:09] (1509.32s)
lot of power to fire people and they put
[25:10] (1510.92s)
a lot of pressure on managers to fire
[25:12] (1512.52s)
people but also the hiring process is up
[25:14] (1514.84s)
to them yeah so that's also who they
[25:17] (1517.16s)
bring on is there it's more free I'm
[25:19] (1519.60s)
sure these things have changed a little
[25:21] (1521.16s)
bit because I think that actually that
[25:23] (1523.08s)
aspect of Netflix's culture has minuses
[25:25] (1525.96s)
as well it's not it's not all pluses I
[25:28] (1528.04s)
think there is definitely some pluses
[25:29] (1529.28s)
and I benefited from some of those
[25:30] (1530.76s)
pluses for sure and initially like when
[25:33] (1533.36s)
I was there I was like wow this is the
[25:34] (1534.72s)
best company ever how many Engineers
[25:36] (1536.60s)
were at the company at the time total at
[25:38] (1538.60s)
Netflix I think like a thousand or maybe
[25:41] (1541.40s)
1500 it's quite a bit bigger now I think
[25:43] (1543.72s)
it's 3K now but yeah it was like yeah
[25:45] (1545.72s)
but definitely like over a thousand got
[25:47] (1547.88s)
it okay but not Facebook size right
[25:50] (1550.16s)
Facebook is like 10 15,000 I was like a
[25:52] (1552.76s)
lot right yeah yeah okay so you
[25:55] (1555.64s)
essentially earned your senior position
[25:58] (1558.60s)
as an ic3 cuz you proved yourself to to
[26:01] (1561.80s)
jender as a junior engineer yeah as a
[26:03] (1563.88s)
junior engineer he thinks okay this guy
[26:07] (1567.52s)
to results yeah and then later when he
[26:09] (1569.72s)
was building up his team it was just a
[26:12] (1572.20s)
matter of oh I know that guy's good I
[26:14] (1574.52s)
want him on regardless of all the level
[26:16] (1576.56s)
stuff yeah I know he's going to deliver
[26:18] (1578.96s)
and I want him on my team and so that
[26:20] (1580.64s)
got you in to get that promotion from
[26:23] (1583.72s)
mid-level to senior yeah okay wow okay
[26:27] (1587.16s)
so internal brand really does matter
[26:29] (1589.40s)
then it matters a lot it matters way
[26:31] (1591.20s)
more than you think and and so that's
[26:33] (1593.56s)
why it's important to like not really
[26:34] (1594.92s)
burn Bridges with people but also find
[26:37] (1597.04s)
those people who you really click with
[26:38] (1598.68s)
and because you never know you might be
[26:40] (1600.52s)
working with them again in the future
[26:41] (1601.92s)
yeah definitely and that was a good jump
[26:44] (1604.36s)
CU if you would have just stayed at
[26:45] (1605.52s)
Facebook you are already greatly
[26:47] (1607.56s)
exceeding so what more yeah you could
[26:49] (1609.68s)
change your behaviors and go through the
[26:51] (1611.56s)
promo process but that would have been
[26:53] (1613.56s)
slower than just going directly into
[26:55] (1615.64s)
Netflix definitely yeah and so was that
[26:58] (1618.24s)
compensation bump from oh yeah it was
[27:00] (1620.04s)
like almost double your compensation
[27:01] (1621.80s)
doubled from I what was it it was like
[27:04] (1624.72s)
two it was like two with L4 to
[27:08] (1628.00s)
385 390 like and but all cash all cash
[27:12] (1632.24s)
wow okay that's pretty good yeah and so
[27:14] (1634.92s)
how was your time at Netflix were you
[27:16] (1636.32s)
thinking I guess they didn't have a
[27:18] (1638.12s)
notion of promotions there CU it's just
[27:20] (1640.28s)
all senior yeah all senior yeah so your
[27:22] (1642.92s)
what was your thinking you wanted to
[27:24] (1644.20s)
transition to software engineer M you
[27:26] (1646.72s)
did that where were you thinking to go
[27:28] (1648.48s)
from there with your career so from
[27:30] (1650.04s)
there I wanted to like I had a vision I
[27:32] (1652.96s)
had a vision of myself it's crazy that I
[27:35] (1655.20s)
walked away from a year ago but like I
[27:36] (1656.72s)
was 24 when I got on Netflix I had a
[27:38] (1658.00s)
vision that I was by the time I was 30 I
[27:40] (1660.88s)
was going to be a principal engineer
[27:42] (1662.24s)
like L7 L8 like and in big Tech doing
[27:46] (1666.04s)
just really technical deep stuff and
[27:48] (1668.20s)
that was my vision and I knew that I was
[27:50] (1670.00s)
not going to get there in data
[27:51] (1671.32s)
engineering and that was one of the
[27:52] (1672.72s)
other reasons why I knew I needed to
[27:54] (1674.32s)
make the switch yeah for sure and
[27:56] (1676.44s)
Netflix was really crazy cuz it was like
[27:58] (1678.48s)
very different instead of doing like
[27:59] (1679.88s)
regular like data pipelines that were
[28:02] (1682.12s)
like once a day processing it was like
[28:03] (1683.68s)
everything had to be in real time to
[28:05] (1685.40s)
detect security threats it was like very
[28:08] (1688.48s)
different very like Cutting Edge very
[28:10] (1690.08s)
like difficult work for sure so then if
[28:13] (1693.40s)
you wanted to get to principle how are
[28:15] (1695.76s)
you going to do that on Netflix great
[28:17] (1697.44s)
question so at Netflix how it works is
[28:20] (1700.56s)
essentially every year there is a
[28:22] (1702.60s)
compensation discussion but again they
[28:25] (1705.00s)
don't have performance reviews either
[28:26] (1706.40s)
there's no performance reviews
[28:28] (1708.12s)
technically there are performance
[28:29] (1709.00s)
reviews at Netflix but they're every
[28:30] (1710.64s)
quarter where your manager gives you a
[28:32] (1712.76s)
color you either get green yellow or red
[28:35] (1715.72s)
as a color where red means you're going
[28:37] (1717.40s)
to be fired imminently yellow means you
[28:39] (1719.76s)
need to pick it up and green means
[28:41] (1721.24s)
you're good you get that feedback every
[28:43] (1723.04s)
quarter which is a lot once a year they
[28:46] (1726.00s)
do have an annual compensation
[28:47] (1727.48s)
discussion but you don't talk about what
[28:49] (1729.60s)
you did it's all about what you could
[28:52] (1732.12s)
get in the market from other companies
[28:55] (1735.04s)
and they they'll match you and but your
[28:56] (1736.64s)
manager could also if they feel like
[28:58] (1738.64s)
you're being underpaid or whatever they
[29:00] (1740.08s)
can also come in and adjust your
[29:02] (1742.24s)
competition like almost at any time it's
[29:04] (1744.44s)
very different a lot fewer rules than at
[29:07] (1747.24s)
meta where it's got to be like every six
[29:08] (1748.84s)
months after a calibration and a packet
[29:11] (1751.24s)
and a submission it's a whole thing
[29:12] (1752.88s)
Netflix is very different but I think
[29:14] (1754.52s)
Netflix has learned because Netflix
[29:16] (1756.48s)
obviously there's levels now and I think
[29:18] (1758.20s)
that was a problem I think for me the
[29:20] (1760.16s)
thing that I recognized and why I didn't
[29:22] (1762.12s)
really care that much about oh there's
[29:23] (1763.84s)
no levels here was one I knew I was
[29:26] (1766.28s)
going to make a ton of money two I knew
[29:27] (1767.84s)
I was working with jender and that I
[29:29] (1769.80s)
knew that I still had so much more to
[29:31] (1771.40s)
learn from I still do because I talk
[29:32] (1772.96s)
with him about entrepreneurship stuff
[29:34] (1774.28s)
now but anyways I had so much to learn
[29:36] (1776.64s)
from him and I was like wherever this
[29:37] (1777.96s)
goes it's going to go and I know I can
[29:40] (1780.40s)
have a good story it comes back to like
[29:42] (1782.64s)
wherever you're at always think about
[29:45] (1785.44s)
your story about the impact that you had
[29:47] (1787.28s)
at the company and what you did and make
[29:49] (1789.60s)
it sound like a movie man make it sound
[29:51] (1791.44s)
cool make it sound like dude you did
[29:53] (1793.20s)
some really cool [Β __Β ] that's like a very
[29:55] (1795.04s)
important part of the journey since I
[29:56] (1796.76s)
have a tendency to leave jobs every two
[29:58] (1798.60s)
years or so I always have to feel like
[30:00] (1800.36s)
I'm satisfied with the story because
[30:03] (1803.00s)
that that's something that happened at
[30:04] (1804.12s)
Airbnb where I actually had an urge to
[30:05] (1805.84s)
quit earlier but then I realized I was
[30:07] (1807.64s)
like wait a minute I don't have a story
[30:09] (1809.24s)
yet I don't have a really good story yet
[30:10] (1810.92s)
so I stayed six more months but yeah
[30:13] (1813.08s)
getting that impact story is super
[30:14] (1814.96s)
important so when you say story you just
[30:17] (1817.04s)
mean a good fully
[30:20] (1820.36s)
delivered package of work that was
[30:22] (1822.72s)
impactful yeah you can sell yep 100%
[30:25] (1825.76s)
exactly where it's like hey if you hire
[30:27] (1827.48s)
me I will do this much for you in two
[30:29] (1829.68s)
years got it okay for instance at meta
[30:32] (1832.76s)
what was your story what did you use to
[30:34] (1834.20s)
sell to okay so at meta I did a a couple
[30:36] (1836.92s)
things one was in notifications I
[30:38] (1838.76s)
developed the reachability metric which
[30:40] (1840.80s)
was a good counterweight to prevent
[30:42] (1842.76s)
spamming on notifications because I
[30:44] (1844.76s)
don't if growth goes up the more
[30:46] (1846.00s)
notifications you send there's a
[30:47] (1847.48s)
correlation there but obviously there's
[30:48] (1848.76s)
a spam on the other side and so
[30:50] (1850.20s)
reachability was like determining who is
[30:52] (1852.76s)
turning off their settings uh which just
[30:54] (1854.44s)
a way more complicated metric than you
[30:55] (1855.84s)
would think so that's one big thing I
[30:57] (1857.12s)
did another big thing was built the
[30:58] (1858.40s)
first crossa growth dashboard for
[31:01] (1861.04s)
WhatsApp Instagram messenger and
[31:02] (1862.40s)
Facebook so you could look at all of the
[31:03] (1863.84s)
growth metrics in one chart and that had
[31:06] (1866.08s)
never been done before was the the
[31:07] (1867.60s)
engineer that integrated all that stuff
[31:09] (1869.32s)
the big thing was Facebook has this
[31:10] (1870.56s)
algorithm called nudges The Machine
[31:12] (1872.08s)
learning Al algorithm that determines
[31:13] (1873.76s)
which notifications to send to you I
[31:15] (1875.56s)
made that pipeline 90 it cost 90% less
[31:19] (1879.24s)
so it was 10 times more efficient after
[31:21] (1881.48s)
I optimized it with this thing called
[31:23] (1883.36s)
sorted merge bucket joins but those are
[31:25] (1885.64s)
the main things that I did in at my time
[31:27] (1887.56s)
at Facebook that I sold to Netflix that
[31:29] (1889.64s)
you're saying for successful job hopping
[31:32] (1892.80s)
you want to wrap those pieces up and be
[31:35] (1895.40s)
thinking about when I jump this is the
[31:37] (1897.96s)
story I'm going to tell about the thing
[31:39] (1899.20s)
that I did yeah because obviously if you
[31:41] (1901.52s)
have short tenure at places the very
[31:43] (1903.28s)
first thing they're going to think is
[31:45] (1905.20s)
this guy doesn't play well with others
[31:46] (1906.72s)
this guy is he's not a good fit there
[31:48] (1908.92s)
why is he going to be a good fit with us
[31:50] (1910.40s)
but you have to squash that very early
[31:52] (1912.64s)
in the interview process you have to
[31:53] (1913.72s)
squash the idea of this guy is a
[31:55] (1915.40s)
disloyal job Hopper because that's
[31:56] (1916.92s)
obviously something they're going to
[31:57] (1917.92s)
think when they look at the resume but
[31:59] (1919.40s)
if you can squash that and instead be
[32:01] (1921.00s)
like no this guy is actually extremely
[32:04] (1924.04s)
ambitious he wants to solve hard
[32:06] (1926.56s)
problems and he has solved hard problems
[32:09] (1929.64s)
and he's on a trajectory to help us
[32:12] (1932.28s)
solve hard problems that is a much
[32:14] (1934.40s)
better more I've even seen it in
[32:16] (1936.44s)
interviews where people were initially
[32:17] (1937.92s)
skeptical of me but after talking with
[32:19] (1939.52s)
me they're like okay this guy seems
[32:21] (1941.24s)
pretty good so let's talk about rvnv so
[32:23] (1943.84s)
I guess for the promotion to senior it
[32:26] (1946.56s)
was through the job hop Contender was a
[32:28] (1948.84s)
big part of it and your ability to sell
[32:31] (1951.28s)
yourself was a big part of it so then
[32:34] (1954.44s)
sounds like Netflix was good what made
[32:36] (1956.24s)
you want to jump to to Airbnb great
[32:39] (1959.00s)
question a couple things happened so
[32:40] (1960.44s)
like one of the things that happened
[32:41] (1961.08s)
with jender was he also believed in me
[32:42] (1962.80s)
too much cuz what ended up happening on
[32:45] (1965.56s)
my team at Netflix was I was on this
[32:47] (1967.72s)
team working on security threat
[32:49] (1969.40s)
detection but then there was a whole
[32:50] (1970.92s)
other team doing this thing called asset
[32:52] (1972.28s)
inventory just us managing all of the
[32:54] (1974.48s)
cloud assets and where they're at and
[32:56] (1976.40s)
who owns all that stuff and the engineer
[32:58] (1978.84s)
there who had been at Netflix for 10
[33:00] (1980.28s)
years left the team there was this
[33:01] (1981.92s)
opening for that spot which was why
[33:04] (1984.64s)
Netflix is complicated back then
[33:06] (1986.48s)
especially complicated that spot was
[33:08] (1988.60s)
definitely a staff spot not a senior
[33:11] (1991.64s)
spot I'm like I'll take it let's go I'm
[33:13] (1993.60s)
hungry for opportunity and I'll take it
[33:15] (1995.60s)
and so I take that role I went from
[33:17] (1997.40s)
interfacing with just the detection team
[33:19] (1999.68s)
to interfacing with 11 other teams the
[33:22] (2002.32s)
amount of conversations that I needed to
[33:24] (2004.20s)
have dramatically skyrocketed I honestly
[33:27] (2007.28s)
wasn't ready for that and I leaned back
[33:29] (2009.24s)
into my behavior okay these people want
[33:31] (2011.40s)
this these people want that and I'm like
[33:32] (2012.72s)
okay I'm just going to answer all these
[33:33] (2013.84s)
people's questions even though I was
[33:35] (2015.00s)
just one guy and it was way too much
[33:36] (2016.44s)
work I got to solve all these problems
[33:37] (2017.60s)
because I was like holy crap this is
[33:38] (2018.68s)
crazy and I got a big raise though I got
[33:40] (2020.88s)
a huge raise from that because of that
[33:42] (2022.68s)
that jump into this new role Netflix
[33:44] (2024.96s)
recognized that so when they when I got
[33:46] (2026.84s)
in I was in like the upper 300s and then
[33:49] (2029.68s)
my next year at Netflix like they had me
[33:51] (2031.56s)
at 550 and because of this like change
[33:54] (2034.40s)
into this kind of more of a staff
[33:56] (2036.28s)
engineer archetype which was not ready
[33:58] (2038.32s)
for and then ultimately what ended up
[34:00] (2040.60s)
happening at Netflix was in
[34:02] (2042.92s)
2019 they decided that data engineering
[34:06] (2046.28s)
and data science so I was still I was a
[34:08] (2048.16s)
software engineer on a data engineering
[34:09] (2049.68s)
team it's complicated okay but like I
[34:11] (2051.48s)
was still in the data engineering orc
[34:13] (2053.04s)
and so the data engineering they
[34:14] (2054.60s)
determined that data engineering was no
[34:16] (2056.64s)
longer like a necessary org and they
[34:19] (2059.48s)
wanted to collapse it into data science
[34:21] (2061.60s)
okay and so they like what they did was
[34:23] (2063.64s)
they straight up they like okay VP fired
[34:26] (2066.84s)
director fir fired and then jender fired
[34:29] (2069.80s)
they just cut the whole chain and then
[34:31] (2071.36s)
they're like okay now all you guys
[34:32] (2072.36s)
report to the data science people now
[34:34] (2074.12s)
and like when they did that when they
[34:36] (2076.96s)
did that like that stressed me out a lot
[34:39] (2079.40s)
it stressed me out way too much I it was
[34:41] (2081.24s)
stressed me out so much that I went on a
[34:42] (2082.60s)
mental health break I went on Mental
[34:43] (2083.96s)
Health break because I was like this is
[34:44] (2084.88s)
too much this is too much and then I
[34:46] (2086.52s)
went on Mental Health break for a month
[34:48] (2088.08s)
then I came back and then I realized I
[34:49] (2089.64s)
was like I wanted to work with your
[34:50] (2090.80s)
tender man like I don't know so he
[34:52] (2092.20s)
wasn't part of the data science or he
[34:54] (2094.64s)
was a data engineering leader oh was he
[34:56] (2096.64s)
fired he was fired yeah no they fired
[34:58] (2098.40s)
all the data engineering leaders oh they
[35:00] (2100.08s)
all got God and then we all started
[35:02] (2102.36s)
reporting to data science leaders
[35:03] (2103.56s)
instead and that was a big thing that I
[35:05] (2105.08s)
was like there was one last I had one
[35:08] (2108.32s)
last attempt that I wanted to do at
[35:10] (2110.52s)
Netflix because technically I also
[35:13] (2113.16s)
wasn't really in the data engineering
[35:14] (2114.80s)
org to begin with I was more in like the
[35:16] (2116.52s)
Cyber Security Org because I was working
[35:18] (2118.28s)
on asset inventory and tracking all like
[35:20] (2120.36s)
the security assets that was like
[35:21] (2121.52s)
literally what my job was and so the
[35:23] (2123.72s)
very last thing I tried was I was like
[35:26] (2126.24s)
tedo's gone I don't want to work in a
[35:28] (2128.08s)
data science org I did that at Facebook
[35:30] (2130.00s)
I did not like it I want to be in an
[35:32] (2132.48s)
engineering org right not an analytics
[35:35] (2135.12s)
org that's why I'm here that's why I
[35:37] (2137.60s)
that was my original reason of coming
[35:39] (2139.36s)
here and so the last thing I did was I
[35:41] (2141.44s)
applied to transition to the cyber
[35:43] (2143.96s)
security team and I was like Hey makes a
[35:46] (2146.12s)
lot of sense I'm like the only software
[35:47] (2147.84s)
engineer on this data engineering team
[35:49] (2149.52s)
so it doesn't even make sense that I'm
[35:50] (2150.68s)
on this team so I think it makes more
[35:52] (2152.04s)
sense that I'm on your guys' team and
[35:53] (2153.28s)
then they were like they didn't that
[35:54] (2154.88s)
transfer they didn't like the idea of
[35:56] (2156.20s)
that transfer and they were like no like
[35:57] (2157.80s)
you should stay in your current role and
[35:59] (2159.20s)
I was like all right Deuces see you
[36:01] (2161.64s)
later and that pissed me off a lot that
[36:03] (2163.12s)
pissed me off a lot because then I'm
[36:04] (2164.16s)
like okay there's what am I supposed to
[36:06] (2166.88s)
do here I'm just supposed to just shut
[36:08] (2168.36s)
up and write pipelines is that what I'm
[36:09] (2169.92s)
supposed to do in this situation when
[36:11] (2171.28s)
literally they just completely changed
[36:15] (2175.08s)
the org in a way that it no longer
[36:16] (2176.68s)
aligns with my career goals so
[36:18] (2178.52s)
ultimately I just quit I was like I'm
[36:20] (2180.68s)
done with nothing lined up I actually
[36:23] (2183.04s)
had a dream of traveling the world
[36:24] (2184.60s)
that's what I wanted to do I wanted to
[36:25] (2185.64s)
spend 2020 travel the world so I quit in
[36:28] (2188.48s)
early March 6th 2020 was my last day of
[36:31] (2191.36s)
Netflix I was like I'm going to travel
[36:32] (2192.76s)
the world the timing was absolutely
[36:34] (2194.52s)
atrocious then the world was like no
[36:36] (2196.08s)
you're not going to travel because Co
[36:37] (2197.68s)
happen and I was like wow okay but yeah
[36:39] (2199.56s)
I just was like I'm done I'm going to
[36:41] (2201.28s)
just not work at this company anymore
[36:42] (2202.84s)
just felt like I wanted to give so much
[36:45] (2205.16s)
to that company they were like we're
[36:46] (2206.48s)
going to give you nothing of what you
[36:48] (2208.72s)
want we'll pay you a lot but we're going
[36:50] (2210.08s)
to give you absolutely nothing else I'm
[36:52] (2212.04s)
like okay then there's the whole adage
[36:53] (2213.84s)
of like in your career you should be
[36:55] (2215.20s)
learning or earning or both I am still
[36:58] (2218.44s)
even today I'm All About Learning is
[37:01] (2221.16s)
still better than earning even now even
[37:03] (2223.56s)
where I'm at that's why I'm like
[37:05] (2225.12s)
entrepreneur now because I want to learn
[37:06] (2226.64s)
new things I want to attack new problems
[37:08] (2228.64s)
and solve new problems and it's that's
[37:10] (2230.28s)
why I got bored at Airbnb because I'm
[37:11] (2231.68s)
like I'm not learning sure I'm making
[37:12] (2232.76s)
great money but I'm not really learning
[37:14] (2234.00s)
so I want to do something else and and I
[37:16] (2236.20s)
think that's not why people work at
[37:17] (2237.96s)
Netflix though they're more motivated
[37:19] (2239.80s)
there to make a lot of money and retire
[37:21] (2241.68s)
early that's the main motivation for
[37:23] (2243.44s)
people there I actually think that
[37:24] (2244.40s)
people at meta are more learning
[37:26] (2246.00s)
motivated yeah for sure okay so yeah
[37:28] (2248.96s)
there was one thing that you said in
[37:31] (2251.32s)
your last story of what you were doing
[37:33] (2253.20s)
in Netflix at the end there y you said
[37:36] (2256.04s)
you got put into a staff role and you
[37:39] (2259.12s)
weren't ready for it yeah I think that
[37:41] (2261.88s)
is the thing that these big tech
[37:44] (2264.20s)
companies try to prevent when they don't
[37:47] (2267.16s)
promote someone because they don't have
[37:49] (2269.52s)
the behaviors but they have the impact
[37:51] (2271.72s)
mhm because you had the skills and
[37:55] (2275.00s)
everything but then you were put in
[37:57] (2277.16s)
there and it was just too much stuff you
[37:59] (2279.80s)
needed the staff behaviors to scale
[38:01] (2281.60s)
yourself and work through other people
[38:03] (2283.72s)
so I thought that was a pretty good
[38:05] (2285.84s)
example of I think when I heard the
[38:08] (2288.12s)
lagging promotion stuff I go why are you
[38:09] (2289.84s)
holding people back yeah but this is the
[38:12] (2292.04s)
exact meant to me prevent this situation
[38:14] (2294.52s)
right where if these people are like
[38:16] (2296.44s)
they have the impact for it but they
[38:17] (2297.92s)
don't have the behaviors like looking
[38:19] (2299.88s)
back on it at Netflix like the big thing
[38:21] (2301.92s)
for me was a couple things I think one
[38:24] (2304.84s)
was establishing better work boundaries
[38:26] (2306.96s)
super important one another one was like
[38:29] (2309.36s)
just like planning things out a little
[38:31] (2311.48s)
bit more and not it's one of those
[38:32] (2312.76s)
things that like I recognize now that's
[38:35] (2315.48s)
actually the part that is again it's the
[38:37] (2317.76s)
lesson I'm learning again as an
[38:39] (2319.00s)
entrepreneur it's the lesson I learned
[38:40] (2320.80s)
then and I'm learning again as you do
[38:42] (2322.08s)
still need to plan things out and be
[38:43] (2323.20s)
like okay this is going to happen later
[38:44] (2324.84s)
it doesn't have to happen today but it
[38:46] (2326.08s)
will happen at some point in the future
[38:47] (2327.84s)
right those things and I think another
[38:49] (2329.60s)
big one was just like selling a vision
[38:51] (2331.92s)
right selling like a technical vision of
[38:53] (2333.60s)
something that was in my head and and
[38:55] (2335.32s)
this is something content has helped me
[38:56] (2336.88s)
a lot with is like being able to take
[38:59] (2339.20s)
ideas that I have in my head that I'm
[39:01] (2341.44s)
very excited about but then actually
[39:03] (2343.04s)
being able to present them and and show
[39:04] (2344.84s)
them and sell other people on them I
[39:06] (2346.52s)
think that's one of the big behaviors
[39:07] (2347.84s)
that changes is that you do need to be
[39:09] (2349.76s)
able to sell you have to be able to sell
[39:11] (2351.44s)
like a vision or a future we need to be
[39:13] (2353.56s)
working on this not that and those are
[39:15] (2355.80s)
things that like in all the previous
[39:18] (2358.04s)
levels of engineering you don't have to
[39:19] (2359.08s)
worry about you just deliver on the work
[39:20] (2360.76s)
that you're supposed to deliver on and
[39:22] (2362.36s)
solve the hard problem but deciding on
[39:25] (2365.00s)
which problem to solve that was the
[39:27] (2367.08s)
other Behavior at Netflix that I was
[39:29] (2369.04s)
like I'm like whoa dude I'm like I don't
[39:31] (2371.76s)
know yeah yeah for sure okay going back
[39:35] (2375.48s)
to the story timeline yeah so now you
[39:37] (2377.96s)
left Netflix cuz there was reorgs chaos
[39:41] (2381.92s)
you don't have anything else lined up
[39:44] (2384.40s)
yep how do you start thinking about
[39:46] (2386.28s)
Airbnb oh yeah it really just came back
[39:48] (2388.40s)
to in December of 2020 when after I was
[39:51] (2391.48s)
like had played a lot of video games and
[39:53] (2393.96s)
I I don't know I just wasn't feeling
[39:55] (2395.56s)
very fulfilled I was really depressed
[39:57] (2397.76s)
and then my my girlfriend at the time
[40:00] (2400.00s)
was like what are you doing with your
[40:01] (2401.60s)
life what's going on and she was like
[40:03] (2403.52s)
very not happy with what I was doing and
[40:06] (2406.04s)
I was like fair and we ended up breaking
[40:08] (2408.44s)
up and I was like whoa this is okay now
[40:11] (2411.16s)
I'm like I got no job I got no
[40:13] (2413.24s)
girlfriend I'm like and I barely got the
[40:15] (2415.56s)
dog getting the breakup but okay we got
[40:17] (2417.32s)
the dog and that's just me and a dog
[40:18] (2418.76s)
right now I'm like I got to freaking
[40:19] (2419.84s)
support my dog at least with an income
[40:21] (2421.64s)
and then I was like I should interview I
[40:23] (2423.52s)
should like I should take another swing
[40:24] (2424.92s)
at the fences here and see what happens
[40:26] (2426.92s)
I also so that was also when I started
[40:29] (2429.60s)
making content was December 2020 was
[40:32] (2432.20s)
like that was because that was also
[40:33] (2433.92s)
something I said to all my co-workers at
[40:36] (2436.36s)
Netflix when I quit I was like you're
[40:38] (2438.64s)
gonna see me again you're gonna see me
[40:40] (2440.40s)
again I'm GNA be famous I promise I I I
[40:42] (2442.76s)
told them all that in like March of 2020
[40:45] (2445.20s)
when I left because I was like I'm going
[40:46] (2446.28s)
to make content I'm going to be I even
[40:48] (2448.24s)
knew back then I was going to make
[40:49] (2449.32s)
content but I should have done it during
[40:50] (2450.84s)
the pandemic when everyone was on their
[40:52] (2452.04s)
phone because you could just blow up and
[40:53] (2453.64s)
then you could be like Ali Miller and
[40:54] (2454.80s)
have 1.5 million followers if you
[40:56] (2456.60s)
started in 2020 you got such an unfair
[40:59] (2459.68s)
advantage and Ali Miller she's like the
[41:01] (2461.48s)
number one AI influencer on LinkedIn but
[41:04] (2464.92s)
yeah I was just happy that I started in
[41:06] (2466.44s)
2020 still and then that was the big
[41:08] (2468.36s)
things I did I started making content on
[41:10] (2470.04s)
LinkedIn and then I started applying I
[41:11] (2471.80s)
actually interviewed at more than just
[41:13] (2473.56s)
Airbnb I interviewed at meta I
[41:16] (2476.24s)
interviewed at Google and I interviewed
[41:17] (2477.84s)
at Airbnb when you interviewed was it uh
[41:20] (2480.56s)
data engineer data engineering roles it
[41:22] (2482.92s)
was a mix actually cuz I didn't know
[41:24] (2484.72s)
what I wanted cuz Airbnb was able to end
[41:26] (2486.80s)
up selling on a data engineering role
[41:28] (2488.72s)
but at Google I interviewed for software
[41:30] (2490.64s)
engineer and at Facebook I interviewed
[41:32] (2492.76s)
for software engineer and I actually got
[41:35] (2495.60s)
offers from all three companies but the
[41:37] (2497.52s)
problem was that the Google and Facebook
[41:39] (2499.84s)
roles were both senior and I was like
[41:41] (2501.96s)
and then every VI was like and I'm like
[41:45] (2505.52s)
okay and then it was just like I was
[41:47] (2507.12s)
like I can't just say no to an extra
[41:49] (2509.40s)
$100,000 because it was just like the
[41:51] (2511.24s)
Airbnb offer was just so much more money
[41:53] (2513.12s)
that it was like okay this is not even
[41:54] (2514.76s)
close do you remember what the numbers
[41:56] (2516.32s)
were yeah so for Facebook it was like
[41:58] (2518.88s)
415 or something like that like it was
[42:01] (2521.00s)
pretty high like 400 and then Google's
[42:03] (2523.92s)
was a little bit like three when I got
[42:05] (2525.40s)
the offer from Google I was like why did
[42:06] (2526.52s)
I even interview with you guys you're
[42:07] (2527.56s)
going to pay me what Netflix paid me
[42:09] (2529.00s)
four years ago I don't know about that
[42:11] (2531.32s)
and then the one from airb came in out
[42:13] (2533.84s)
was like and I was like okay it's much
[42:15] (2535.20s)
more over $100,000 more and I was like
[42:17] (2537.56s)
okay freaking easy decision easy
[42:20] (2540.36s)
decision yeah no brainer yeah it made me
[42:22] (2542.80s)
a little bit sad cuz I was like it's not
[42:24] (2544.08s)
even really competing offers because
[42:25] (2545.96s)
those ones aren't even really comp
[42:27] (2547.16s)
competing with the other one and I was
[42:28] (2548.28s)
like it was an interesting of place to
[42:30] (2550.32s)
be but the reason why I was okay with it
[42:33] (2553.04s)
because Airbnb actually does data
[42:35] (2555.28s)
engineering very differently than uh a
[42:37] (2557.56s)
lot of other companies big things like
[42:40] (2560.60s)
for example at Airbnb I only coded in
[42:43] (2563.04s)
Scala right no Sequel and I guess not
[42:46] (2566.32s)
only Scala but like 95% Scala and 5%
[42:49] (2569.36s)
python but because it's all about they
[42:51] (2571.24s)
want really high quality pipelines that
[42:52] (2572.72s)
are integrated with their online systems
[42:54] (2574.80s)
like with for me it was pricing and
[42:56] (2576.28s)
availability their pric availability
[42:57] (2577.88s)
systems they wanted pipelines that
[42:59] (2579.44s)
emulated all of the behavior that those
[43:02] (2582.12s)
systems would create and that's what I
[43:04] (2584.64s)
worked on and I'm like this is not
[43:06] (2586.32s)
really even this is a good it actually
[43:08] (2588.96s)
felt very amazing at first because I was
[43:10] (2590.96s)
like this is exactly what I wanted at
[43:12] (2592.76s)
Netflix cuz I'm like it's the perfect
[43:14] (2594.24s)
blend of creating pipelines but also
[43:16] (2596.32s)
still having technical Integrations and
[43:18] (2598.44s)
optimization concerns that you have to
[43:20] (2600.00s)
also think about and dealing with online
[43:22] (2602.04s)
systems it was like this crazy like role
[43:24] (2604.08s)
that was in the middle that I really
[43:25] (2605.24s)
liked but yeah it was an interesting one
[43:27] (2607.20s)
for sure so Airbnb gives you staff
[43:31] (2611.24s)
that's a no-brainer and it makes it so
[43:33] (2613.16s)
that you're willing to go back in the
[43:35] (2615.16s)
data engineering software engineering
[43:36] (2616.76s)
okay sounds good the big question for me
[43:40] (2620.64s)
is how are you able to sell them on
[43:42] (2622.40s)
staff because you were senior if you
[43:44] (2624.40s)
just were to go for a staff interview
[43:46] (2626.68s)
there's some requirements of certain
[43:48] (2628.24s)
number of years of experience or those
[43:50] (2630.80s)
types of blocking things that you might
[43:52] (2632.16s)
not have control over so how do you get
[43:54] (2634.20s)
interview and great question CU that was
[43:55] (2635.84s)
actually something that I was really
[43:57] (2637.72s)
stunned by with airb because that
[43:59] (2639.80s)
interview they were actually
[44:01] (2641.04s)
interviewing me for one or the other
[44:02] (2642.96s)
they were like we might give you senior
[44:04] (2644.40s)
we might give you staff they were saying
[44:06] (2646.00s)
like based on how you interview and I
[44:07] (2647.32s)
was like because I actually got the
[44:09] (2649.48s)
offers from uh Facebook and Google first
[44:11] (2651.80s)
and then I got the Airbnb one and cuz I
[44:13] (2653.52s)
was like ah dude because when those two
[44:15] (2655.16s)
came in at senior I'm like like Airbnb
[44:17] (2657.88s)
don't do it don't do don't do me don't
[44:19] (2659.44s)
do me like this but then Airbnb comes in
[44:21] (2661.24s)
his staff and I'm like okay then that
[44:22] (2662.64s)
makes it very easy and you're totally
[44:24] (2664.24s)
right the role the staff role at least
[44:25] (2665.84s)
on the job description says 10 plus and
[44:28] (2668.16s)
at that point I had six and I'm like 10
[44:31] (2671.12s)
plus and six that's that's there's a gap
[44:32] (2672.92s)
there there like a significant Gap I
[44:35] (2675.08s)
think it comes back to just that impact
[44:37] (2677.00s)
story and being able to talk about what
[44:38] (2678.76s)
I did at Netflix and like the being like
[44:41] (2681.08s)
I interfaced with these like 11 teams
[44:42] (2682.84s)
and we solved all these crazy security
[44:44] (2684.96s)
problems right being able to just talk
[44:46] (2686.72s)
about all that stuff that is uh what I
[44:49] (2689.80s)
think really put airb be over the edge
[44:52] (2692.28s)
because one of the things that I feel
[44:54] (2694.00s)
very grateful from Netflix that I know
[44:56] (2696.36s)
impressed people people at Airbnb was
[44:58] (2698.68s)
they have this kind of culture of this
[45:00] (2700.32s)
feedback culture right the radical
[45:02] (2702.12s)
cander of just give feedback immediately
[45:04] (2704.52s)
right it's like almost if you come from
[45:07] (2707.84s)
a a Kinder company or a more chill
[45:10] (2710.08s)
company when you come into Netflix and
[45:11] (2711.92s)
then you start getting this immediate
[45:13] (2713.36s)
feedback you're like everyone here's a
[45:15] (2715.52s)
dick everyone here's like why is
[45:16] (2716.80s)
everyone here so mean but then after a
[45:18] (2718.64s)
while you're like wait a minute no
[45:19] (2719.72s)
everyone here really wants me to grow
[45:21] (2721.44s)
that's what it's actually about and I
[45:23] (2723.48s)
think that was what I was able to learn
[45:25] (2725.60s)
from and get that but I was definitely
[45:28] (2728.08s)
really nervous about the role at Airbnb
[45:30] (2730.56s)
because I was like am I just walking
[45:32] (2732.60s)
right back into what I just left at
[45:34] (2734.12s)
Netflix right am I walking right back
[45:35] (2735.92s)
into something that it was going to be
[45:38] (2738.36s)
just a replication of what I was doing
[45:40] (2740.24s)
before for the senior and the staff was
[45:42] (2742.28s)
the recruiter up front where they're
[45:43] (2743.60s)
saying Hey FYI you're either going to be
[45:46] (2746.32s)
senior staff good luck on the interviews
[45:48] (2748.72s)
yeah they they actually did say that and
[45:50] (2750.08s)
I was annoyed by that a little bit
[45:52] (2752.28s)
because I just felt I'm like I guess
[45:54] (2754.60s)
because I knew that at that moment if it
[45:56] (2756.64s)
was just a senior interview I wasn't
[45:58] (2758.68s)
going to take it because was there
[46:00] (2760.20s)
something on your end that you did to
[46:02] (2762.64s)
advocate for staff oh yeah great
[46:04] (2764.76s)
question so I advocated for staff
[46:07] (2767.28s)
because in in that interview I was like
[46:09] (2769.24s)
hey I'm interviewing at these other
[46:10] (2770.40s)
companies and when I was talking with
[46:12] (2772.08s)
the the Airbnb recruiter I was like hey
[46:14] (2774.16s)
I'm interviewing at Facebook and at
[46:16] (2776.00s)
Google right now as well and those
[46:18] (2778.12s)
companies like if and I even told him
[46:20] (2780.28s)
I'm like if I get an interview from all
[46:21] (2781.52s)
three of you and they all come in at
[46:23] (2783.48s)
senior I'm not picking Airbnb you said
[46:26] (2786.24s)
that to yeah
[46:27] (2787.52s)
right so were they gonna do senior yeah
[46:29] (2789.60s)
I think so I I think that was well the
[46:31] (2791.32s)
interview they said that's why we leaned
[46:33] (2793.04s)
into that kind of Middle Ground of we'll
[46:34] (2794.64s)
just do the interview and if you
[46:36] (2796.12s)
interview well enough because I wanted
[46:37] (2797.92s)
it to be like an open-mindedness at
[46:39] (2799.76s)
least of give this guy a chance but yeah
[46:42] (2802.28s)
because otherwise because everything
[46:44] (2804.04s)
being equal I probably would have gone
[46:45] (2805.84s)
back to Facebook if it was like senior
[46:47] (2807.84s)
across the board I probably would have
[46:49] (2809.36s)
gone back to Facebook got it like but
[46:51] (2811.28s)
since it was not I was like and did you
[46:53] (2813.04s)
try to get staff interviews at Google
[46:54] (2814.52s)
and Facebook too yeah I did try to get
[46:56] (2816.48s)
those they did not give me that straight
[47:00] (2820.12s)
out at the front they said senior only
[47:02] (2822.12s)
but Airbnb they said oh probably senior
[47:05] (2825.48s)
you said I'm not going to take it unless
[47:08] (2828.04s)
staff's an option and then they said
[47:09] (2829.84s)
okay maybe staff and then you had the
[47:11] (2831.88s)
opportunity and you did well on the
[47:13] (2833.00s)
interviews yeah okay yeah it was wild
[47:14] (2834.80s)
and I love that that's why it's so
[47:16] (2836.64s)
important to have more than one company
[47:18] (2838.56s)
that you're interviewing for that you're
[47:19] (2839.76s)
excited about because then that puts you
[47:21] (2841.56s)
in this position where you can have
[47:22] (2842.88s)
conversations where hey this is what I
[47:24] (2844.52s)
need from this company and because
[47:26] (2846.88s)
otherwise I'm gone I'm just going to go
[47:28] (2848.36s)
somewhere else and how many years of
[47:30] (2850.36s)
experience did you have at that point
[47:32] (2852.08s)
six yeah it was six actually I had a
[47:33] (2853.68s)
viral post on LinkedIn about this where
[47:35] (2855.52s)
the Airbnb rooll said I needed 10 and I
[47:38] (2858.20s)
applied and it was six and I got it and
[47:40] (2860.48s)
then my whole point on that post was
[47:42] (2862.04s)
like apply for jobs that you don't think
[47:43] (2863.96s)
you're ready for yeah yeah yeah so your
[47:46] (2866.20s)
ability to negotiate and sell is what
[47:49] (2869.88s)
got you that that stuff okay definitely
[47:52] (2872.64s)
and actually like after being in that
[47:55] (2875.28s)
role for a little bit I was ready for it
[47:58] (2878.16s)
because you want to know what I realized
[47:59] (2879.72s)
I realized more about the Netflix role
[48:03] (2883.80s)
was more problematic than I thought it
[48:06] (2886.92s)
was it was that I changed ladders right
[48:11] (2891.48s)
I went from data engineer to software
[48:13] (2893.00s)
engineer but then I went up that ladder
[48:14] (2894.68s)
to staff and so in some ways like I was
[48:17] (2897.24s)
just not ready to do software
[48:18] (2898.56s)
engineering at that staff level because
[48:20] (2900.52s)
honestly I'd been doing it like
[48:22] (2902.08s)
professionally one year and the only
[48:24] (2904.44s)
reason that I was able to like even not
[48:26] (2906.32s)
just get absolutely crushed was because
[48:27] (2907.88s)
I'd been spending all my weekends doing
[48:29] (2909.44s)
it and like doing side projects and and
[48:31] (2911.24s)
hustling on the side but if you look at
[48:33] (2913.20s)
the actual professional experience it
[48:34] (2914.92s)
was the combination of those two things
[48:36] (2916.44s)
that I think was like brand new like job
[48:38] (2918.92s)
role but also higher job title and those
[48:41] (2921.96s)
two things together was like burnout
[48:44] (2924.00s)
risk whereas like when I got in at
[48:45] (2925.48s)
Airbnb it was like staff data engineer
[48:47] (2927.40s)
I'm like okay I feel pretty good about
[48:49] (2929.28s)
this it was like more the leadership was
[48:51] (2931.40s)
there and I was like okay I needed to
[48:52] (2932.84s)
grow in there a little bit but it it was
[48:54] (2934.44s)
more manageable it didn't feel like it
[48:56] (2936.32s)
wasn't like oh my God I have so much to
[48:58] (2938.28s)
learn it was like okay there's things I
[49:00] (2940.04s)
need to learn but I know what they are
[49:02] (2942.08s)
and this is going to be doable that was
[49:04] (2944.44s)
what I want to ask you is now because
[49:06] (2946.48s)
you went into the staff role some might
[49:08] (2948.76s)
wonder would you underperform in that
[49:11] (2951.12s)
role you're saying that you performed
[49:13] (2953.16s)
fine because it was going back to data
[49:15] (2955.28s)
engineering which you had a lot more
[49:16] (2956.56s)
confidence in is that right yeah and
[49:18] (2958.56s)
that because I think at Netflix it was
[49:20] (2960.00s)
the combination of getting put into this
[49:22] (2962.84s)
position of high-risk position of and
[49:25] (2965.80s)
like leadership ship position when I
[49:27] (2967.80s)
wasn't ready for it but then it was the
[49:29] (2969.84s)
combination of that and that I
[49:32] (2972.28s)
transitioned to software engineering
[49:33] (2973.92s)
like less than a year before and so
[49:35] (2975.56s)
those two things together were I think
[49:38] (2978.56s)
where there was a gap right where it's
[49:40] (2980.16s)
you only want to change like one
[49:41] (2981.52s)
variable at a time and then so when I
[49:44] (2984.08s)
got in at Airbnb and I was nervous about
[49:46] (2986.52s)
it for sure super nervous because I was
[49:47] (2987.68s)
like I don't want to just run myself
[49:49] (2989.32s)
right back into the ground being in a
[49:51] (2991.04s)
position where I'm like I am not ready
[49:52] (2992.68s)
for this but it was ended up being way
[49:54] (2994.88s)
more chill for sure yeah and then your
[49:57] (2997.44s)
first year at Airbnb how was the
[50:00] (3000.08s)
performance yeah I got exceeds my first
[50:02] (3002.56s)
half at Airbnb and it was a good one
[50:04] (3004.52s)
like I think that first year I really
[50:08] (3008.24s)
started to get the I just up leveled a
[50:10] (3010.96s)
lot of the pricing pipelines and then I
[50:13] (3013.60s)
built a lot of designs it was a lot
[50:15] (3015.96s)
higher level kind of stuff and then they
[50:17] (3017.76s)
also wanted me to they said I was close
[50:19] (3019.28s)
with greatly because the problem was
[50:20] (3020.76s)
architecture stuff right they really
[50:22] (3022.00s)
wanted me to be working on things that
[50:23] (3023.68s)
were companywide and I just wanted to
[50:25] (3025.68s)
work on Marketplace they wanted me to
[50:27] (3027.52s)
design the best practices of how to take
[50:29] (3029.68s)
data from the data Lake and put it back
[50:32] (3032.48s)
in the production systems because
[50:34] (3034.52s)
everyone has taking data from production
[50:36] (3036.40s)
putting it in the lake that's going the
[50:37] (3037.96s)
other way is not as like straightforward
[50:40] (3040.92s)
and they wanted me to come up with all
[50:42] (3042.16s)
those and I just had no desire to do
[50:44] (3044.48s)
that and then and that's when I realized
[50:46] (3046.36s)
that was a moment there I had a Moment
[50:47] (3047.84s)
of clarity I remember it was in
[50:48] (3048.92s)
September of 2021 when I was like wait a
[50:51] (3051.44s)
minute do I even want to get promoted am
[50:53] (3053.52s)
I good where I'm at right now do I not
[50:55] (3055.16s)
even care cuz I don't know I just feel
[50:57] (3057.08s)
like I'm someone who like I want to do
[50:59] (3059.64s)
everything that is asked of me and I
[51:01] (3061.08s)
want to always be showing that next
[51:02] (3062.48s)
level growth that's like a part of my
[51:04] (3064.12s)
life and when I didn't want to do that I
[51:06] (3066.72s)
literally was like I don't want to do
[51:08] (3068.16s)
this work I don't want to do it and I I
[51:09] (3069.80s)
told my manager I'm not going to do this
[51:11] (3071.08s)
work and they're like okay that they
[51:12] (3072.36s)
even told that if you don't want to do
[51:13] (3073.84s)
that work that's the work that would get
[51:15] (3075.60s)
you promoted that's the work that's
[51:16] (3076.72s)
going to get you to the next level but I
[51:18] (3078.12s)
just don't care it's too many meetings I
[51:19] (3079.96s)
just did not like the fact that it was
[51:21] (3081.24s)
just so many meetings so did your cuz
[51:24] (3084.16s)
you said earlier your vision for your
[51:26] (3086.00s)
career was as principal engineer by age
[51:29] (3089.16s)
did that change then cuz cuz they were
[51:31] (3091.04s)
handing you they were handing me the
[51:32] (3092.60s)
path right up for sure that's exactly
[51:34] (3094.20s)
what they were doing and I think it was
[51:36] (3096.36s)
when I recognized this was also right
[51:39] (3099.00s)
when I was getting traction on LinkedIn
[51:41] (3101.08s)
at the same time I was like that's I
[51:42] (3102.64s)
just hit 50k on LinkedIn or something
[51:44] (3104.16s)
like that I was like wait a minute I
[51:46] (3106.12s)
actually care about other things now I
[51:47] (3107.84s)
don't just care about my job I care
[51:49] (3109.52s)
about this other stuff as well and so I
[51:51] (3111.96s)
told my manager I'm like it's fine I
[51:53] (3113.52s)
will just work my job and that was like
[51:55] (3115.76s)
my goal was like wanted to just get
[51:57] (3117.28s)
Airbnb to more of a rest invest kind of
[52:00] (3120.28s)
situation where I'm just doing the
[52:02] (3122.60s)
absolute bare minimum what I wanted to
[52:04] (3124.40s)
do throughout your story at Facebook and
[52:07] (3127.76s)
at Netflix you had a really strong
[52:10] (3130.16s)
internal brand with your manager and so
[52:13] (3133.08s)
I think opportunities came to you he
[52:14] (3134.76s)
kept giving you stuff get you to go
[52:16] (3136.60s)
higher and higher yeah it sounds like a
[52:18] (3138.44s)
Airbnb even without that manager's trust
[52:23] (3143.52s)
people again were giving you opportunity
[52:26] (3146.08s)
so what did you do at Airbnb to go from
[52:28] (3148.64s)
zero internal brand to a point where
[52:31] (3151.24s)
they're saying here's senior staff
[52:32] (3152.96s)
please help us oh oh that's a great one
[52:34] (3154.64s)
this is one of the things that I try to
[52:35] (3155.76s)
do every time I get a new job is I want
[52:38] (3158.52s)
to do something in three months where
[52:41] (3161.08s)
people are like damn they're like okay
[52:44] (3164.12s)
this guy's crazy and the thing that I
[52:45] (3165.52s)
did in in three months at Airbnb was so
[52:49] (3169.52s)
they have this pipeline called the
[52:52] (3172.08s)
pricing and availability pipeline that
[52:53] (3173.64s)
computes all the prices and availability
[52:55] (3175.40s)
every day and it was like a mess it was
[52:59] (3179.08s)
like one of the most like deaddy
[53:01] (3181.28s)
freaking pipelines I have ever seen they
[53:03] (3183.56s)
had this new notion called the paved
[53:05] (3185.16s)
road which is the way you're supposed to
[53:06] (3186.80s)
build a pipeline that is compatible with
[53:08] (3188.56s)
the platform high quality and all they
[53:10] (3190.64s)
had given me that to move that pipeline
[53:12] (3192.64s)
onto the road but they said that was
[53:14] (3194.32s)
something finished by the end of the
[53:15] (3195.48s)
year I finished it in the first quarter
[53:17] (3197.48s)
instead of four quarters and they were
[53:20] (3200.00s)
like okay this guy clearly knows how to
[53:22] (3202.32s)
make things a lot better and because
[53:24] (3204.12s)
that made it so pipeline was no longer
[53:25] (3205.80s)
delayed pipeline just worked and
[53:27] (3207.80s)
everything was just smooth and pretty
[53:29] (3209.16s)
much Flawless going forward and that was
[53:31] (3211.44s)
the start of that first that's the first
[53:33] (3213.68s)
like trigger in like someone's brain
[53:35] (3215.28s)
because they're like first off they're
[53:36] (3216.72s)
like this guy didn't just ramp up really
[53:39] (3219.04s)
quickly he ramped up and landed a big
[53:42] (3222.00s)
impact quickly those two things together
[53:44] (3224.16s)
are are really important where I want to
[53:45] (3225.88s)
show them that I don't really care that
[53:47] (3227.36s)
much about risk right that like I manage
[53:49] (3229.60s)
risk really I know that this pipeline is
[53:51] (3231.96s)
very important for the whole company
[53:54] (3234.44s)
it's a price is a very important part of
[53:55] (3235.96s)
Airbnb
[53:56] (3236.96s)
and so I was like we can figure this out
[53:58] (3238.56s)
and we're going to build this out and
[53:59] (3239.64s)
I'm just going to be very careful and
[54:01] (3241.40s)
follow all the best practices and let's
[54:03] (3243.44s)
get this done I try to do that I I try
[54:05] (3245.56s)
to find those points in systems where
[54:07] (3247.84s)
people know that things could be a lot
[54:09] (3249.84s)
better but they don't want to touch it
[54:11] (3251.96s)
because it's too risky or too complex or
[54:15] (3255.00s)
too much of a pain in the ass it's
[54:16] (3256.72s)
usually one of those three and that that
[54:18] (3258.52s)
that's why people just let it be bad or
[54:20] (3260.28s)
let it be suboptimal and there's I know
[54:23] (3263.20s)
I have a gift for finding those points
[54:24] (3264.88s)
of like where it's okay I can this
[54:26] (3266.76s)
problem but I don't know if this is the
[54:28] (3268.44s)
right one to solve but I'll do it and I
[54:29] (3269.84s)
want to land an impact early that's the
[54:31] (3271.64s)
big thing to start building that brand
[54:34] (3274.04s)
and did you know that work would have
[54:36] (3276.36s)
the impact before you did it or was that
[54:38] (3278.44s)
kind of handed to you or so it was
[54:40] (3280.08s)
handed to me obviously it's handed to
[54:41] (3281.76s)
you when you if if you're three months
[54:43] (3283.28s)
into a job like everything is handed to
[54:45] (3285.12s)
you at that point right it takes at
[54:46] (3286.92s)
least six months before you can build
[54:48] (3288.64s)
your own internal kind of compass of the
[54:52] (3292.08s)
company where you sit especially in
[54:54] (3294.60s)
these big companies that like have so
[54:56] (3296.44s)
any moving parts that's the only way to
[54:57] (3297.84s)
do it but in this case it was like it
[54:59] (3299.88s)
was something that was handed to me but
[55:01] (3301.28s)
I think it's an interesting kind of
[55:02] (3302.60s)
trade-off right and the goal there is
[55:04] (3304.56s)
just to build that brand when you're
[55:05] (3305.92s)
starting a new job people don't trust
[55:07] (3307.48s)
you they honestly don't trust you some
[55:08] (3308.68s)
people might actually distrust you I
[55:10] (3310.20s)
know that there were some senior
[55:11] (3311.48s)
engineers at Airbnb who actually didn't
[55:13] (3313.40s)
like me because I got hired in that
[55:14] (3314.56s)
staff because they were like they've
[55:15] (3315.88s)
been gunning for staff and like that
[55:17] (3317.36s)
staff promo from senior to staff is just
[55:21] (3321.00s)
unnecessarily ridiculous at most
[55:23] (3323.24s)
companies right and then they they
[55:25] (3325.32s)
thought it was just handed to me cuz I
[55:26] (3326.64s)
got hired in there and they're like oh
[55:28] (3328.00s)
why is this external hire getting this
[55:29] (3329.56s)
one I've been grinding for 4 years
[55:31] (3331.40s)
trying to get this promo yeah that shows
[55:33] (3333.48s)
to the value of interviewing because you
[55:35] (3335.84s)
did something that very impressive too
[55:39] (3339.00s)
you you did it and you got this offer
[55:41] (3341.68s)
with like less than six months of work
[55:44] (3344.36s)
whereas these other people they go
[55:45] (3345.68s)
through all the hoops and things and
[55:47] (3347.44s)
yeah still they're having troubles I
[55:49] (3349.04s)
guess it shows the value of interview
[55:50] (3350.56s)
it's similar to a couple things I think
[55:52] (3352.24s)
a couple other pieces of that are like
[55:54] (3354.12s)
you know how when like startup companies
[55:55] (3355.96s)
are Venture Capital pre-revenue
[55:58] (3358.00s)
companies actually get more generous
[56:00] (3360.24s)
offers because it's the maybe right it's
[56:02] (3362.72s)
like where could this go but then it's
[56:04] (3364.88s)
like when you have a track record the
[56:06] (3366.88s)
inertia that you have built from your
[56:09] (3369.00s)
own track record it's hard to overcome
[56:12] (3372.08s)
even if it's great still can be hard
[56:14] (3374.00s)
because they're going to always be like
[56:15] (3375.32s)
we hired you at this level and then you
[56:16] (3376.92s)
have to fight it upwards that's why yeah
[56:18] (3378.64s)
interviewing is wild yeah I think cuz
[56:20] (3380.68s)
there's more variance in the interview
[56:22] (3382.56s)
process There's an opportunity for you
[56:24] (3384.08s)
to step you get that stepwise right it's
[56:26] (3386.76s)
not an angle change it's a step change
[56:28] (3388.60s)
yeah that's huge okay so that kind of
[56:30] (3390.56s)
does the whole story of ic3 to ic6 and
[56:33] (3393.96s)
what you did two halves at Facebook you
[56:36] (3396.44s)
did about two halves at at Netflix you
[56:39] (3399.36s)
had a break for roughly a year so you
[56:41] (3401.20s)
basically went from Junior to staff in
[56:44] (3404.16s)
three three four years yeah that's
[56:47] (3407.12s)
insane okay so I think a few questions
[56:49] (3409.28s)
wrap up the interview yeah one of the
[56:51] (3411.24s)
most common ones that I get is how much
[56:53] (3413.32s)
did you work it sounds like you're
[56:55] (3415.28s)
working about 60 hours hours especially
[56:57] (3417.72s)
60 hours a week at Facebook and Netflix
[57:00] (3420.48s)
what about Airbnb was that Airbnb was a
[57:02] (3422.48s)
lot better in
[57:03] (3423.92s)
2021 like 40 maybe a little bit more
[57:06] (3426.80s)
like that was one of the things that
[57:08] (3428.04s)
blew my mind about getting the exceeds
[57:10] (3430.16s)
yeah because I was like I'm not even
[57:12] (3432.56s)
what I was like I I I actually thought
[57:14] (3434.44s)
that my initial read on that was like
[57:18] (3438.64s)
wait a minute you can get exceeds and
[57:20] (3440.80s)
just work a normal amount of hours that
[57:23] (3443.00s)
was something that I didn't didn't even
[57:25] (3445.00s)
think was possible I thought I was going
[57:25] (3445.96s)
to get Meats I thought I was going to
[57:26] (3446.92s)
get meats and I'm like great I'm I'd be
[57:28] (3448.56s)
happy with Meats I'm fine just don't
[57:29] (3449.96s)
fire me I've definitely met people who
[57:32] (3452.08s)
are afraid of the staff promotion
[57:34] (3454.56s)
because they think that it locks them
[57:36] (3456.76s)
into a lot greater than 40 hours a week
[57:39] (3459.48s)
this is proof that in many CA or at
[57:41] (3461.32s)
least in this one case you don't need to
[57:44] (3464.60s)
work more than 40 hours a week and you
[57:46] (3466.80s)
can meet expectations it's more about
[57:48] (3468.88s)
shifting your behavior right it's about
[57:50] (3470.40s)
shifting from you really need to be able
[57:52] (3472.24s)
to start identifying High leverage
[57:54] (3474.44s)
opportunities right and that's not
[57:56] (3476.24s)
necessarily something that is grindy
[57:58] (3478.24s)
right that's just something that like
[57:59] (3479.80s)
you need to learn how to do and I think
[58:01] (3481.64s)
that it can be grindy for some people in
[58:03] (3483.32s)
staff and I think that's why some people
[58:04] (3484.64s)
like they do feel like they need to like
[58:06] (3486.36s)
work more but also sometimes like those
[58:08] (3488.24s)
opportunities are just not there too
[58:10] (3490.00s)
It's Tricky yeah definitely I think one
[58:13] (3493.16s)
of the things that might be interesting
[58:15] (3495.28s)
to go over is there something you
[58:17] (3497.52s)
think's unique to your personality that
[58:20] (3500.68s)
kind of helped you throughout yeah
[58:22] (3502.20s)
that's a good one I think a couple
[58:23] (3503.96s)
things there like the biggest one for me
[58:26] (3506.24s)
is just my tenacious ability to just
[58:30] (3510.92s)
keep learning and and I'm willing to put
[58:32] (3512.96s)
in the work to do it cuz even when I was
[58:35] (3515.16s)
doing 60 hours a week at Facebook I also
[58:38] (3518.96s)
founded a startup during that time and
[58:40] (3520.88s)
then Saturday and Sunday at the same
[58:43] (3523.00s)
time I was also working on a startup
[58:45] (3525.12s)
then because I wanted to learn
[58:46] (3526.56s)
JavaScript and I wanted to get better at
[58:48] (3528.04s)
full stack development I wanted to learn
[58:49] (3529.72s)
how to do all stuff which has been
[58:50] (3530.96s)
critical for My Success this year as an
[58:52] (3532.76s)
entrepreneur because now I have this
[58:54] (3534.40s)
platform that's all JavaScript based and
[58:55] (3535.84s)
I'm like I'm so happy that I did that
[58:57] (3537.88s)
even though back then I was like this is
[58:59] (3539.84s)
my whole life I'm just sitting in front
[59:01] (3541.44s)
of a computer and oh my God this is so
[59:03] (3543.24s)
crazy I think that's one thing I think
[59:05] (3545.44s)
another angle that I think is important
[59:07] (3547.40s)
for me is that I'm a positive person I
[59:09] (3549.88s)
think that another thing that's very
[59:10] (3550.96s)
important is being excited to work like
[59:13] (3553.04s)
showing up to work and being like I'm
[59:14] (3554.60s)
excited to be here I'm happy to be here
[59:16] (3556.48s)
is an underrated trait because the thing
[59:18] (3558.76s)
is if you are showing enthusiasm and
[59:20] (3560.48s)
excitement it's contagious it makes
[59:22] (3562.00s)
other people like their jobs more and if
[59:24] (3564.20s)
they like their jobs if they like their
[59:25] (3565.80s)
jobs more because of you they like you
[59:27] (3567.88s)
and if they like you they're more likely
[59:29] (3569.24s)
to give you opportunity and that helps a
[59:31] (3571.20s)
lot I know that's my friend nikot she's
[59:33] (3573.40s)
doing crazy good at meta and I think
[59:36] (3576.08s)
that like for her that's a big part of
[59:37] (3577.32s)
it too is just like being able to get
[59:38] (3578.64s)
people to like you and trust you and
[59:40] (3580.96s)
build up especially as you get into
[59:42] (3582.32s)
leadership and manager I feel like it's
[59:44] (3584.28s)
like a manager's entire job is that
[59:46] (3586.72s)
right is is is to get you to like your
[59:48] (3588.84s)
job and so I think that's going to be
[59:51] (3591.12s)
the other big one I think there's one
[59:53] (3593.40s)
other angle that I think is for me I
[59:55] (3595.80s)
don't know if being positive is unique
[59:57] (3597.40s)
about me but I think the third angle
[59:59] (3599.28s)
that I think for me is that I am not
[60:03] (3603.08s)
willing to put up with [Β __Β ] like when I
[60:05] (3605.84s)
think something is unfair I'm willing to
[60:08] (3608.68s)
change my life than just deal with it
[60:12] (3612.04s)
which I think is a double-edged sword I
[60:13] (3613.68s)
think I don't think that it's
[60:14] (3614.72s)
necessarily always a good thing I think
[60:16] (3616.52s)
that there could have been I think I
[60:18] (3618.24s)
could have done like a similar career
[60:19] (3619.76s)
trajectory as you if I would have just
[60:21] (3621.12s)
stayed at meta and found another manager
[60:23] (3623.40s)
who was better and pushed that way and
[60:26] (3626.12s)
probably would have been like less
[60:27] (3627.40s)
chaotic for me like in terms of all
[60:29] (3629.44s)
these new companies all these health
[60:30] (3630.84s)
insurance plans all these 401ks you know
[60:32] (3632.84s)
how many 401ks I had to get because of
[60:34] (3634.80s)
all this like it's had to merge all of
[60:36] (3636.56s)
them it's pain in the ass that's still
[60:39] (3639.08s)
the same thing though cuz even at meta
[60:41] (3641.60s)
you'd have to not be satisfied with your
[60:43] (3643.76s)
current one and be willing to switch
[60:45] (3645.32s)
teams which is yeah still taking a risk
[60:48] (3648.12s)
being okay with risk is a very important
[60:50] (3650.84s)
part of this journey for sure yeah and I
[60:53] (3653.32s)
think that first trait is a large part
[60:55] (3655.56s)
of why your first manager even trusted
[60:57] (3657.76s)
you so much if you have someone on your
[61:00] (3660.64s)
team that's willing to put in those
[61:02] (3662.80s)
insane hours or have that impact yeah
[61:05] (3665.60s)
the manager is going to keep trusting
[61:06] (3666.76s)
you with more if if you can show your
[61:08] (3668.36s)
manager that you're going to stick with
[61:09] (3669.56s)
a problem until it's solved yeah yeah
[61:11] (3671.40s)
then they're like okay yeah here's more
[61:13] (3673.00s)
work here's more important work yeah
[61:15] (3675.16s)
cool and then last thing is if you were
[61:17] (3677.76s)
to start all over again as ic3 knowing
[61:20] (3680.72s)
what you know today MH what's one thing
[61:23] (3683.84s)
that you change ooh that's a good one I
[61:26] (3686.24s)
think that there's a couple angles there
[61:28] (3688.44s)
one is
[61:32] (3692.40s)
like more open to more perspectives
[61:37] (3697.68s)
because I feel like my first couple
[61:40] (3700.52s)
years in big Tech I was just very
[61:41] (3701.92s)
focused on I need to just get my tech
[61:43] (3703.76s)
skills up very high just become like the
[61:45] (3705.76s)
most technical person ever and now
[61:49] (3709.00s)
recognizing that that really only
[61:50] (3710.96s)
matters to get to senior engineer for
[61:53] (3713.64s)
the most part like after that like
[61:55] (3715.96s)
technical skills do help a little bit
[61:58] (3718.36s)
but it's more marginal after senior
[62:00] (3720.28s)
engineer you need other skills to get
[62:02] (3722.64s)
past that and feel like I didn't really
[62:05] (3725.72s)
start to develop a lot of those soft
[62:08] (3728.08s)
skills until I was at Netflix and things
[62:10] (3730.76s)
were on fire and that's when I was like
[62:12] (3732.84s)
okay time to learn the soft skills right
[62:14] (3734.92s)
when I need them like when I desperately
[62:17] (3737.28s)
need them and I think had I spent a
[62:19] (3739.28s)
little bit more time at Facebook
[62:20] (3740.60s)
focusing on those things developing the
[62:22] (3742.56s)
soft skills in lower risk situ
[62:27] (3747.36s)
so that like failure doesn't feel so
[62:30] (3750.12s)
crazy that is I think something that
[62:32] (3752.68s)
would have helped me a lot have a better
[62:34] (3754.60s)
work life balance and probably grow
[62:36] (3756.28s)
faster in my career I think that is a
[62:38] (3758.12s)
big one that I definitely would have
[62:39] (3759.56s)
changed I think another one I would have
[62:41] (3761.12s)
changed that is important is don't eat
[62:44] (3764.92s)
dinner at work don't do it just don't
[62:47] (3767.32s)
eat dinner at work it's a scam dude it's
[62:49] (3769.52s)
a scam because they offer it because
[62:53] (3773.16s)
they get an Roi right that's the only
[62:55] (3775.52s)
reason and Facebook and Google all these
[62:58] (3778.20s)
companies they do not offer you dinner
[63:00] (3780.20s)
because they're just beautiful amazing
[63:03] (3783.40s)
great companies the only reason it's
[63:04] (3784.92s)
there is to keep you at the office
[63:05] (3785.88s)
longer and to get you working more live
[63:07] (3787.88s)
your life take those hours right because
[63:10] (3790.08s)
I think that was another thing because I
[63:11] (3791.48s)
didn't really get into fitness until
[63:13] (3793.40s)
2018 like my first year at Netflix and I
[63:16] (3796.08s)
feel like had I taken those hours back
[63:18] (3798.92s)
and dedicated them to the gym or
[63:20] (3800.84s)
dedicated them to other areas of my life
[63:23] (3803.16s)
that would have been another way that
[63:24] (3804.60s)
things could have been so given your
[63:26] (3806.60s)
super fast career growth are you saying
[63:29] (3809.32s)
that you wish you worked less though and
[63:31] (3811.56s)
was it worth it or the career growth I
[63:33] (3813.44s)
think is worth it because it's another
[63:36] (3816.52s)
way to go about doing your life my
[63:38] (3818.60s)
vision now of my life is more of a
[63:40] (3820.44s)
vision of balance and a a vision of
[63:42] (3822.64s)
tranquility and peace I'm trying to
[63:45] (3825.00s)
manifest that in my life now I wouldn't
[63:47] (3827.20s)
want to do it again now right I wouldn't
[63:49] (3829.12s)
want to go back and do what I did from
[63:51] (3831.24s)
22 to 25 do those three years again no I
[63:54] (3834.12s)
wouldn't want to do it again but do I
[63:55] (3835.96s)
regret it no I think that it was what I
[63:58] (3838.20s)
needed at the time to feel powerful it's
[64:00] (3840.16s)
what I needed at the time to grow into
[64:02] (3842.84s)
the person I'm supposed to be but with
[64:04] (3844.72s)
that being said your health matters a
[64:06] (3846.24s)
lot and I think that's an angle that
[64:07] (3847.80s)
people forget about when they're like do
[64:09] (3849.24s)
TC chasing is that okay but it's okay
[64:11] (3851.84s)
say you make $20 million or whatever
[64:14] (3854.20s)
working in big Tech but you stressed out
[64:15] (3855.96s)
the whole time and you get cancer and
[64:17] (3857.28s)
you die when you're 50 it's that a good
[64:18] (3858.84s)
life you got to be thinking about those
[64:21] (3861.00s)
other angles right health wealth
[64:22] (3862.76s)
happiness they all matter and at
[64:24] (3864.80s)
different points in your life they
[64:26] (3866.04s)
matter different amounts that's why
[64:27] (3867.68s)
looking at it now it's different but I
[64:29] (3869.92s)
think that it's a strategy so it's if
[64:31] (3871.32s)
you want that's definitely a way to go
[64:33] (3873.24s)
if you want to go really and honestly I
[64:36] (3876.08s)
think as especially young men who are
[64:38] (3878.12s)
seeking purpose working really hard is a
[64:40] (3880.84s)
great option it's actually a really
[64:42] (3882.56s)
great option because it makes you useful
[64:44] (3884.84s)
it makes you useful because like when
[64:46] (3886.12s)
you're a teenager you're not really
[64:48] (3888.00s)
useful and you got to learn and grow and
[64:49] (3889.52s)
build something that makes you useful
[64:51] (3891.28s)
for society and that is I think it gave
[64:53] (3893.92s)
me a sense of purpose and that's great
[64:55] (3895.88s)
but could I have gotten that sense of
[64:57] (3897.12s)
purpose without grinding so hard and
[64:59] (3899.24s)
having so many like sleepless nights and
[65:01] (3901.24s)
so many like nights where I felt like I
[65:03] (3903.24s)
was in over my head and a couple panic
[65:05] (3905.36s)
attacks you there's a lot of other kind
[65:06] (3906.92s)
of behind the scenes things there that
[65:08] (3908.52s)
weren't really talked about like growing
[65:10] (3910.68s)
the career that like I think are
[65:13] (3913.08s)
important that things that like aren't
[65:15] (3915.36s)
discussed as much so if you could go
[65:17] (3917.08s)
back and talk to ic3 Zack yeah you'd say
[65:21] (3921.08s)
stop being one-dimensional but still
[65:23] (3923.04s)
keep working hard at at work but make
[65:24] (3924.80s)
sure you take care of your health
[65:26] (3926.60s)
and enjoy the ride more enjoy the ride
[65:28] (3928.44s)
more and not get laser focused on that
[65:30] (3930.48s)
and Laser focused on I must get promoted
[65:32] (3932.60s)
it's everything will come to you in time
[65:34] (3934.64s)
right if you put in the hours every day
[65:36] (3936.84s)
and you're showing up every day you'll
[65:39] (3939.08s)
get what you want the universe gives you
[65:40] (3940.84s)
exactly what you want if you're willing
[65:42] (3942.24s)
to put in the work and pay the price
[65:44] (3944.28s)
thanks so much for your time Zach really
[65:46] (3946.00s)
appreciate you coming on the podcast if
[65:47] (3947.76s)
you made it this far thanks for
[65:49] (3949.12s)
listening I am going to start posting
[65:52] (3952.04s)
these career story podcasts since I
[65:54] (3954.64s)
think it's helpful to to learn from
[65:56] (3956.64s)
others' experience when I was growing
[65:59] (3959.20s)
the staff I had a lot of help from
[66:01] (3961.32s)
mentors who shared this kind of
[66:03] (3963.04s)
information with me in one-on-one
[66:05] (3965.24s)
conversation so I'm hoping this podcast
[66:07] (3967.84s)
can make that information more
[66:09] (3969.28s)
accessible when I asked to interview
[66:11] (3971.40s)
Zach I wasn't fully prepared for the
[66:14] (3974.20s)
video side of things we just recorded
[66:16] (3976.32s)
this with our smartphones it's not the
[66:19] (3979.32s)
best but it serves as a good starting
[66:21] (3981.96s)
point uh for us to improve from so yeah
[66:24] (3984.84s)
we were literally crammed right behind
[66:27] (3987.12s)
me in my tiny room in SF but yeah it was
[66:29] (3989.88s)
fun and if you have any feedback for me
[66:31] (3991.84s)
on how to make this podcast more helpful
[66:34] (3994.52s)
I'd love to hear it in the comments I'll
[66:36] (3996.36s)
read every comment that I get here and
[66:39] (3999.20s)
yeah thanks for listening once again
[66:40] (4000.68s)
appreciate it