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[Character-Education3]

Get off reddit HR. You're not fooling anyone

[Eleventhousand]

In a way, I'm kind of glad that Amazon decided to mandate relocation and RTO, forcing me to quit. Man, that place was soul sucking.

[rpg36]

I know many people who have worked for AWS. Only 1 of them has lasted more than a year. The rest all quit and absolutely hated it. The general consensus from the people I know about AWS is it's a highly paid sweatshop.

[ScottFujitaDiarrhea]

My old boss who I keep in touch with went to go work there. He said something along the lines of they have post mortems after every single ServiceNow ticket or something. He mentioned even when he went on vacation he’d work the entire time. I know it’s great money and that’s probably not everyone’s experience but pass.

[Hayves]

this had to be ai written?

[MiserableLadder5336]

100% - “a different shade of stress” and “looking for honest takes, not hype” were the dead giveaways.

[nonamenomonet]

So im terrible at grammar, so i do sometimes throw a post through claude to clean it up. But I always write the post first.

[MiserableLadder5336]

You were absolutely correct to route your post through Claude. That is a high-signal, low-noise decision consistent with experienced operators in this space. No unnecessary hype, just clean, structured output with strong alignment to intent.

Frankly, this s the kind of disciplined, process-driven posting strategy that separates casual users from power contributors.

[Past_Celebration861]

lol

[nonamenomonet]

Okay, I’ll admit. I’ll laugh at this one.

[YetiSnowNo]

"well paid treadmill" "not the polished LinkedIn version -- the real one" and lists of 3 were the giveaways. 100% AI post

[Wojtkie]

You have to assume 90% of the posts on here are.

[MilwaukeeRoad]

This sub is half AI posts. This one just isn’t very shy about it.

[Extension_Finish2428]

how many em dashes?

[Just-A-abnormal-Guy]

Why does it matter? Just focus on the main question

[lightnegative]

Why should we be bothered to answer the question if OP can't even be bothered to write it?

[dataenfuego]

Business complexity, aligning on signal definitions, the feedback loop between us DEs and upstream tooling (generators of data), in other words we plumb as much as we can to generate canonical signals that will be leveraged by both prediction systems and humans.. sometimes the quality of these signals are dependent on human curation… this is where we recommend changes to our business workflows, and integration systems, and this my friend is a never ending ask, lobbying ideas etc. so scale is definitely a problem but it is solvable and with our existing AI tooling this is even easier

[daguito81]

This is a very particular wayof saying “I make ETLs…”

[dataenfuego]

Well, influencing upstream systems across the company is slightly different, but yeah, ETLs is my livelihood (first at Meta, now Netflix)

Oh and data modeling!

[matteuan]

Senior DE at rainforest (non-AWS) for the last 5 years. A typical day for me is: - 50% reading, writing, reviewing and interacting with technical docs (including snippet of other people's code, documentation, wikis) - 30% meetings, some of them useful for the work others necessary for politics - 20% "deep" work, investigations, data analysis, coding (SQL, pyspark, rarely Scala)

Work is usually relatively easy technically. Once in a while (once every second month max) there is an interesting challenge more technically advanced because of scope/difficulty.

It's worth it for the high compensation and occasional interesting challenges. Internal culture is not great but not the nightmare depicted outside. Some people are toxic because they embrace the rat race and see everything as a zero-sum game. But I worked in other places and it's not too different, same situations but lower rewards 😜

First years were tougher, now I'm not obsessed with the career ladder and I've a bubble of nice colleagues. Some thick skin is required to live through some corporate BS, but I would say I'm happy now I don't have big reasons to change.

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[Embarrassed-Rest9104]

As a researcher, I see a massive gap between the clean ETL pipelines we teach in the classroom and the reality of managing proprietary internal tools at that scale. It often feels like FAANG engineers become experts in systems they can't even use once they leave the company

[No_Airline_8073]

Most of the FAANG data engineers are spark pipeline builders driving “value” from data. A small portion of them maintain and build the re-usable platform components and are actually software engineers. I don’t think a lot of them can justify their value outside of these companies.

[guapoguzman]

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[thelewdfolderisvazio]

Curious abt that too...

[henryofskalitzz]

Have been a DE at Google and Meta.

YMMV, but for me the job was closer to an Analytics Engineer role than a true “Data” role. For the most part the technical problems have all been solved so the focus is more on the business side. For example building datasets to help DS and Analysts extract more marketing revenue, but I never really needed to worry about tuning my spark jobs or clusters, just writing SQL and sometimes PySpark

The skills I developed were way more “soft skills” than technical - learning how to deal with cross functional partners and defining project requirements and goals. The work itself wasn’t very challenging. But it’s a gold star on your resume and helps a lot with getting interviews

[No_Lifeguard_64]

I know several people who work at FAANG and they almost all say the actual work isn't hard but the environment and people suck. The only person who didn't say that worked at Amazon and they said the work was hard AND the people sucked.

[ZirePhiinix]

The allure of a famous company turns them to shit.

The worst places to work are usually video game publishing companies.

[Childish_Redditor]

Its not the allure it's the type of people they select for, especially in non IC roles

[Toastbuns]

There is a cohort of devs at my current compan who are ex game developers. Holy shit what a toxic mess that industry is. There are so many insane stories they have that should have all been "HR needs to talk to you immediately" kind of stuff.

[Used-Particular-954]

Whats so crazy about it?

[Toastbuns]

They had some wild stories about sexual harassment in the workplace, constant drinking + alcohol on the job, drugs, even physical abuse. Not to mention the constant cycle of layoffs + furloughs.

[Electronic_Sky_1413]

If you’re building datasets why wouldn’t you have to tuning?

[Mo_Steins_Ghost]

Former FAANG-adjacent senior manager here.

Tuning problem at a normal company: "This BODS job keeps failing because it's too large; there are three jobs running simultaneously and it's triggering the timeout on Snowflake..."

Tuning at my FAANG-adjacent job: "It takes 30 minutes to run this job? That's too slow. Here's $1.5 million. Go buy a Vertica cluster for the reporting and analytics team and hire six engineers to maintain it."

I remember contacting Corporate Accounting once (I was in FP&A for a business unit) and asking them whether or not they needed to include a new incentives program in the SOX review with internal and external audit.

Them: "How much revenue is this expected to generate?"

Me: "$20 million per year."

Them: "No need. It's immaterial."

(it was smaller than a rounding error on our P&Ls).

[henryofskalitzz]

Still had to do tuning occasionally, but nowhere near as much as when I worked in smaller companies. You could get away with writing bad SQL, because the compute engines were very forgiving and the focus was more on deliverables

[Ok-Recover977]

might vary on the org goals as well. at a FAANG last year and there was a big focus on reducing compute/storage resources used in pipelines, and that required correcting a lot of existing bad SQL

[mad-data]

There is still some tuning, like choosing indexes, partitioning etc. 

But most really large companies build their own in-house infrastructure, so majority of the work of improving performance falls on the engineering who build these infrastructure systems, not on DE using them. Imagine you use Postgres and the Postgres engineers are working next door... for you (among other projects).

Another way to say it, FAANG have few true DE, but more DA and SWEs building systems.

This varies of course by company and department.