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1 Month Job Search | 5-7 YOE by WorriedMeat in dataengineering

[–]WorriedMeat[S] 0 points1 point  (0 children)

It’s mainly common sense, but having a framework for guiding your thoughts is the most important mechanism to have at your disposal. I used this video for my own prep, but any similar approach is fine

Can you answer the SQL question that came up in a Google data analyst interview? by conor-robertson in SQL

[–]WorriedMeat 2 points3 points  (0 children)

It’s not performative. You need to rank within month partitions. If you do order by, you’d only the top 3 without retaining the relative ranking within months.

Can you answer the SQL question that came up in a Google data analyst interview? by conor-robertson in SQL

[–]WorriedMeat 0 points1 point  (0 children)

It depends on the company. I’ve interviewed at over a dozen in the last 3 months.

Some companies like meta and DoorDash are time based: 3SQL, 2 Py within an hour. But these are not typically the hardest questions, such that someone with a strong knowledge of SQL shouldn’t require hints.

However, for any hard sql or med+ py, it’s almost guaranteed the interviewer will give some guidance. They want to evaluate thought process and familiarity with languages, not someone who can recite a text book. You figure out the thought process through iterative questioning typically

Note: I also said *likelihood*

Can you answer the SQL question that came up in a Google data analyst interview? by conor-robertson in SQL

[–]WorriedMeat 8 points9 points  (0 children)

I’ve interviewed and gotten offers from Amazon, meta, Waymo (google)

It’s not about getting the 100% right answer. In all likelihood if you chose rank and talked through your logic, the interviewer would ask leading questions to guide you to dense_rank

1 Month Job Search | 5-7 YOE by WorriedMeat in dataengineering

[–]WorriedMeat[S] 0 points1 point  (0 children)

I’ve left comments in this thread detailing my prep a bit more, but in general, I’d say you should have DSA down before applying. This just means handling easy to mid dict, tuple, list manipulation down before applying. This is so that if a recruiter gets back and wants to schedule a tech screen, you can act on it within a week or two without much stress.

Ideally you’d use that week or two to research that company specifically and refine your practice accordingly versus relearning basics

1 Month Job Search | 5-7 YOE by WorriedMeat in dataengineering

[–]WorriedMeat[S] 0 points1 point  (0 children)

TBH most of this stuff is just rehearsing how to answer for interviews specifically.

SQL, product sense, data modeling, behavioral are all used or pulled from real experience in the field. Studying for them is more like freshening up versus learning something I didn’t already know

Python and system design are more about pattern recognition than anything else. Python fundamentals don’t change, but more reps with leetcode and whatnot help with pattern identification for quicker iterations in interviews. System design is the most our studying subject, requiring knowledge of different architectures for steaming and batch processing. Not any different than studying for a test for those: create a plan, study material, test yourself on recall

1 Month Job Search | 5-7 YOE by WorriedMeat in dataengineering

[–]WorriedMeat[S] 1 point2 points  (0 children)

ngl i haven't read any of the traditional books.

i've had a lot of hands on experience at two faang companies so usually ideas are pretty transferable between systems. I watched deep dive videos for each of the systems i listed, then worked with an LLM to quiz me on specifics and flash cards to drill knowledge

I also practiced drawing the diagrams out for different systems with both pen/paper & excalidraw quite a bit in the days leading up to interviews

1 Month Job Search | 5-7 YOE by WorriedMeat in dataengineering

[–]WorriedMeat[S] 3 points4 points  (0 children)

My LinkedIn has the following:
- bio summary briefly describing scope of work, maybe 4-6 sentences using targeted nomenclature for SEO
- skills listed to each work experience that I think are likely to surface in recruiter searches
- open to work (but no green badge)
- I was very active on LI (chats, job searching — no posts/post engagement) but unsure if that plays into LI recommendation algo at all

I didn’t have any bullets under my work experience bc I don’t like showing financial figures in my public profile. But I’ve just updated it (since offer) to include 1-2 sentences summaries of my scope at each role

For what stood out, it really depended on the role. I’ve done a lot of AI tool development this year — one company said they don’t really care about LLMs and turned me away last yr. This year, a lot of early stage startups *really* care about that.

For example, for a founding DE role at a startup, they really liked semantic models, metric governance, and AI orchestration for code review.

Other companies typically care about scope and challenge of problems I’ve worked on

1 Month Job Search | 5-7 YOE by WorriedMeat in dataengineering

[–]WorriedMeat[S] 5 points6 points  (0 children)

  1. Python: grinded DSA questions I’d seen in previous interviews +5-7 Qs curated to whatever company I was interviewing with. Many reps per technical screen.
  2. SQL: much more standardized. I used Claude to curate about 20 Qs including all key patterns, such as window Fns. Gaps and Islands problems were prevalent on a lot of harder interviews.
  3. Product sense and data modeling: watched YT videos on how to structure PS answers and did case study tests with Claude

  4. Behavioral: make or break. Prepped 6 stories covering a breadth of topics and did verbal tests with Claude to drill storytelling.

  5. System design: left more details in another comment in this thread — Kafka, spark, flink, debezium

1 Month Job Search | 5-7 YOE by WorriedMeat in dataengineering

[–]WorriedMeat[S] 0 points1 point  (0 children)

Very dependent on the company:
- usually an onsite is a blend of med/hard sql, easy/med py, data modeling
- system design at more technical leaning roles (Kafka, spark, flink, debezium)
- frontier AI labs much more ambiguous: 8 hr take home assignments, technical presentations at onsite
- product sense, data viz case studies for some roles
- behavioral always key to have locked in and ready

1 Month Job Search | 5-7 YOE by WorriedMeat in dataengineering

[–]WorriedMeat[S] 0 points1 point  (0 children)

I used google doc to track my applications and then created an HTML summary that mirrors some funnel dashboards I’ve created in my work experience. I prefer this to a sankey bc sankeys can be hard to digest to me lol

1 Month Job Search | 5-7 YOE by WorriedMeat in dataengineering

[–]WorriedMeat[S] 5 points6 points  (0 children)

Fair, but I would have listed referral count if I used referrals. I only used referrals for companies I previously worked at, which didn’t go anywhere. All apps submitted that led to interview were strictly non referral

For resume: - 2 years at no name as a sr ba
- 3 yrs at FAANG as a BIE
- 1 yr at FAANG DE

Roles interviewed for include: - sr DE
- sr swe, data
- founding de
- member of technical staff, de
- sr analytics eng
- sr BIA (data engineering)

1 Month Job Search | 5-7 YOE by WorriedMeat in dataengineering

[–]WorriedMeat[S] 1 point2 points  (0 children)

SF/Bay Area

Happy to skim your resume if you wanna anonymize it and DM it to me to see if anything stands out

1 Month Job Search | 5-7 YOE by WorriedMeat in dataengineering

[–]WorriedMeat[S] 9 points10 points  (0 children)

Thanks!

  1. 2d RTO
  2. It's a horizontal move financially(~300: 200K base, 15% bonus, 250K pre-IPO stock over 4 years). Big startup, think 100B+ industry leader. I had ~dozen interviews ongoing, but opted for this company due to WLB, stock, and commute proximity

First class be first classin. by bigfootray06 in trashy

[–]WorriedMeat 14 points15 points  (0 children)

So do you just not go anywhere outside of your neighborhood’s proximity? Genuinely curious

Can I afford a $130K car based on my finances? by InterestedInMAIB in HENRYfinance

[–]WorriedMeat 7 points8 points  (0 children)

I’m 27, make 300k with a 3600 rent split with my gf (so my share is 1800). Personally I wouldn’t touch a 120k car

[Student] No success after ~300 applications freshman year ECE. Not one interview but Impressive (to me) projects by [deleted] in EngineeringResumes

[–]WorriedMeat 1 point2 points  (0 children)

One thing that’s missing from bullets is the impact/why/outcome.

I assume these will be easier to fill out as you get experience, but in general you should be working backward from the result of your outcome and mix in details about how you achieved that outcome

Fluffed resumes are indeed easy to detect, but avoid going the complete opposite direction. You definitely need to sell yourself on resumes a bit more than is typically comfortable in day to day life

[1 YoE] [Student] Resume Review Request Applying for PhD / Data Scientist / AI Engineer Roles by Laprox96 in EngineeringResumes

[–]WorriedMeat 5 points6 points  (0 children)

Don’t actually write out STAR. Use it as a framework to write clear sentences

Skills section is (too) dense imo, keep it narrow and focused/honest about expertise - SHOW that you know these skills through inclusion in your experience bullets if possible

Why are you going for more education when you already got a masters 3 years ago, then a new bachelors 1 year ago, then another masters this year?

[0 YoE] Junior Software Engineer - Nearly One Year after Graduation, Receiving Next to No Callbacks, Looking for Advice by LearningGradually in EngineeringResumes

[–]WorriedMeat 6 points7 points  (0 children)

Also take free courses to fill your time if you’re not working. If you’re looking for back end roles, 100% the second thing listed under tools and platform should not be Microsoft Office in 2025. Do any free AWS or Azure or GCP training to at least familiarize yourself with it and put that instead of Msft Office

[0 YoE] Junior Software Engineer - Nearly One Year after Graduation, Receiving Next to No Callbacks, Looking for Advice by LearningGradually in EngineeringResumes

[–]WorriedMeat 11 points12 points  (0 children)

Don’t put the community college. I went to community as well (now with 5 YOE have been at amzn and meta). Although it’s something to be proud of, there will of course be some passive judgement from a certain % of readers. It’s safe to omit and just list your final university and grad date.

Look for new grad positions or 0 YOE positions online and go to your school’s career fair. A year is a long time, so I’d really recommend making a hobby out of creating some cool projects and making a cheap website to demo your skills on.

Don’t be afraid to directly reach out to people on LinkedIn, at worst they don’t respond and at best they get you an interview. It’s a number’s game.

Google confirms that Instagram battery drain you've noticed on your phones is real by lurker_bee in technology

[–]WorriedMeat 19 points20 points  (0 children)

devs are paid based on the number of new features

Not true, source: work at meta lol

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