Trying to evaluate two offers (FB, Apple) vs. staying at Uber. There's no clear best decision in my mind so curious for the community's thoughts. Caveat: I feel tremendously thankful to have any options at all given the current economy. I find myself in the fortunate position of evaluating multiple options, so just seeking some input. In an ideal world I'd like to optimize for flexibility, TC, mission, enjoyment, and career growth. Option 1. Stay at Uber, Sr Product Analyst, TC ~350k including stock growth Pros: + Possibly more stock growth in future? + Current comp, super flexible WLB + Possibly more career opportunity given half the company was fired or quit? + Don't lose social capital I've accrued + Can mostly buy into the product + No switching costs (handling more changes during covid, losing flexibility I've carved out in current setup, remote onboarding, rolling dice on new team, trading one companies problems for another's) + Mostly like people on my team Cons: - Been a tough ride the past couple years. Morale is less bad, but still not great IMO - Just not jazzed about the work on my team right now - Career growth continues to be very unclear - Stock kinda sucks - Lack of Data Engineers at Uber really kills the effectiveness of DS/PA role. Not sure I want to work within that system anymore. Option 2: Facebook, Data Engineer IC5, TC 305k + 50k signon Pros: + Super flexible company from what I can tell. Remote options, relatively flexible WLB. + Seems to have very strong data culture and vision compared to e.g. Uber. + Was generally impressed with the quality of recruiter and more senior folks I met. ("Peer" interviewers not as much) + Continued stock growth seems likely based on past 10 years. Refreshers are also supposed to be strong. + DEs seem to have lots of freedom compared to Eng (lots of structure) or DS (lots of adhoc) Cons: - Is it evil? Harder for me to buy into product. - Recent uncertainty due to antitrust, etc. - Risk of not knowing team in advance due to bootcamp - DE hiring was weirdly easy. Out of all companies I've applied to, FB was by far the easiest. Makes me feel like this is a role to avoid. - DE is a different career path - Possibly lower comp than Uber after Year 1, but lots of uncertainty at any company about refreshers, etc. Option 3: Siri @ Apple, Data Scientist, TC TBD (still waiting on recruiter) Pros: + People at Apple seem generally happy and stay for a long time + Possibility to have noticeable impact on Siri + Mostly impressed by interviewers + Recruiter expected offer to come in higher than FB + Stock growth has been strong Cons: - Questionable WLB. HM didn't do much to dissuade this notion - Ambiguous bonus/refreshers - Role seems *very* product-y for DS. Not much in the way of technical development - Internal movement seems difficult due to secrecy. HM even mentioned this. - Not a fanboy. Thought they were awesome in early 2000s, but have lost a bit of the "magic" to me in recent years - Is Siri going to be good someday? Will voice assistants ever be widely adopted? - "Release schedule" and strict data privacy rules seem to hamper innovation - Iffy data culture from what I can tell - Stock seems ridiculously high right now #facebook #apple #dataengineer #analytics #datascience #career #offer
What was the FB DE interview like? I thought that would be close to a SWE interview or did they just ask SQL with some questions to gauge data infra knowledge? I’d go to Apple. Uber’s lack of DE like you mentioned makes data there really frustrating
Nowhere near swe. I've heard product de is different than infra though. I'll fill in some details later tonight
On site was 2 etl rounds, 1 data modeling round, and 1 ownership round (thirty mins) focused on behavioral. Etl rounds started with product discussion, eg defining metrics. Then followed by sql and python questions. Sql was nothing too complicated. Similar to tps difficulty. Python was relatively easy. I don't remember the exact questions but would say probably LC easy with no discussion of edge cases, unit testing, big O, etc. I even started discussing that my brute force solution could be improved upon and they didn't really care. Data modeling round starts with non-fb product discussion. Metrics, data you'd like to collect. Then you should be able to discuss star vs snowflake and why you're choosing one over the other (hint: you're building an analytical db not a data warehouse). You'll design some basic tables and columns, then be asked to write sql with the pretend data to calculate some basic metrics. Pretty basic sql required. That was it. And from what I can tell, sql is the main skill needed for the job. Doesn't sound like python is even used that much.
YOE & FB DE breakup?
8 yoe. Fb offer was 185, 380/4, 15%, 50 sign on
Years in Uber? If cliff is far away I’ll stay
Come interview at Netflix. Def higher TC. Lots of growth ahead. Amazing DEs and great infrastructure. Lots of freedom to use whatever tech stack you want to solve a problem. Otherwise I'd take FB or Uber. Uber has lots of upside post covid. FB will be fine even with antitrust attention. Apple beauracracy will eat you alive. Don't do it
Hi allyurbase,can I dm you for more information
Hi allyurbase, may I know what skillsets are mandatory to interview for DE opportunities with Netflix. I dont have Big Data/Cloud Experience but have heavy SQL + little Python experience along with ETL tools. Do you think I have a chance to at least interview?
Congrats on great offers, could you please share insights on the interview process for Apple? I’ve DM’d you! Thanks
I'll be honest, I don't know how to do DMs on Blind! I've looked all around but still not sure. Feel free to educate me if you know how though.
You can reply here itself? About your Apple DS process
Would you mind sharing what your initial offer was for your Uber role excluding stock growth? I didn’t think it could get that high for L5 PA even with stock appreciation
135k base / 144k over 4 RSUs / 20k cash bonus (no sign on, target refresh of 42k) -> TC of 191k
My base increased to 143k within a few months of joining b/c my mgr told me recruiting had lowballed most of my team. I don't now how he got it adjusted. And then increased again to 151k last cycle. My cash bonus was about 1.5x for 2019. My refresh was another 150k / 4 grant, but I also got a discretionary grant of 90k / 2. Then the Horizon grant (which was pretty small actually).
Could you give a bit of insight into the 2 ETL parts for Fb DE onsite? How are they different? Do they ask to build end-to-end pipelines using Python OR are they straight leetcode like questions? Not sure how a leetcode style question may fit into an ETL round though. Thanks!
It's all getting a little fuzzy at this point, but i'll try. If i remember correctly, both were focused on facebook products but different ones. there was initial jamming with the interviewer on how to measure the product. e.g. we talked about the process of sharing a photo on facebook, what metrics I'd want to collect to see if it's doing well, what i would measure if i wanted to improve it, etc. edge cases came up around whether a user can go backwards in the process within a session and how that would affect the measurement. i think that lasted 15-20 mins and then we jumped into some sql related to what we'd just discussed, and some python that was sort of related to something a DE might face. it wasn't ETL related or anything - i think it was more about manipulating data and calculating metrics using standard libraries only (no pandas, numpy, etc). so know how to read a csv into a data structure of your own design (and know why you chose that design) and how to calculate metrics off of it.
Thanks much for sharing! really helpful..
FWIW I stayed at Uber.
Hey OP, congrats on the great offers despite you decided to stay at Uber. This is one of the best posts on ds pa so far! Do you mind sharing your interview preparation process? How did you price case/metrics/ab test questions? I have decent sql experience but been failing case questions on the analytical and thought articulation. Thanks for the help in advance! I can also dm
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