Data Engineering at Apple just isnt what I thought itd be

PearceN9714·August 5, 2026

I come from a largely swe oriented experience and I just feel like the role of data engineering at Apple is too restricted, automated, and very non-developer friendly. While building pipelines can be enjoyable, the whole dashboard development process is just a bunch clicking. And beyond that, the things I care about (building data tooling, automating insights, taking over logging) doesnt really seem to be the kind of impact upper level DE management seems to care regarding when it comes to performance reviews.

The biggest message they try to give us is that they dont hope us to be “SQL Monkeys” and they want us to be “Full Stack Data Engineers.” But in practice, this really just means build pipelines for analytics and dashboards based on the data generated by those pipelines. In essence, their idea of a “Full Stack Data Engineer” is nothing more than a “SQL Monkey that has sign language capabilities.” If anything, our gig comes out to be maybe 85-90% BI (Business Intelligence) and 10-15% Engineering. This is really in stark contrast to how the position is marketed and made out to be.

Without turning this into a full blown rant (assuming it isn’t already one), I think I’ll leave this by saying, perhaps I require a career change. But beyond that, im kinda interested to see what other engineers’s thoughts are on this. Ive largely just expressed these thoughts in isolation or with a few close colleagues, so Im interested to break away from my echo chamber a bit and hear other thoughts.

P.S. Its my initial ever datadriven post too 😁

20 comments

fond_viper_3068·

I read DE was born out of BI at Apple. Look up the article Rise of DE.

PearceN9714op·

Yes!!! This was a blog post I read when initial applying. The author (Maxime Beauchemin) actually also worked at Apple as a DE (he was one of the initial DEs there too). He left, actually, to gig for Stripe where he wrote the first version of Airflow (there was an in house tool at Apple he modeled it off of actually). That article was one of the things that got me hyped about the position.
But just as a side note, the author also wrote a piece regarding a year later called The downfall of the Data Engineer where he highlights some of the same struggles I listed out.

sleek_robin_6897·

From what I can tell, DEs at FB are what you earn of it. The main issue is that when XFNs think of DEs, they believe "Dashboards". So that's the main request you'll get from each XFN and you'll be supporting those.
This likely differs from team to team but at least on the products that I'm aware of, the more proactive you are, the more options you have available to you that goes beyond just dashboarding. Building pipelines can sound really mundane especially if what you need to build is already laid out, but there's a ton of opportunities to use the pipelines you build to drive products and influence your XFNs too. A solid DE is often pretty much a TPM that aligns SWE and DS together.
If you're feeling tired of just building pipelines and dashboards I highly recommend trying to get more involved with your SWE teams if they're developing fresh features -- there's always a lot of fun work around there you can do.

fond_viper_3068·

Yep I read the follow up article too. Good that you are on top of it. Hows DS and ML area at FB ? You don’t wanna take that route ?

PearceN9714op·

So I do a fair bit of interviews for practice and it really does seem like people care regarding the fact that I was at FB (they don’t particularly care that I was DE), so that brand name recognition is definitely worthwhile.

ANALOGquartz08·

No worries, lots of folks went to FB DE in similar situation as you. Luckily it seems u ha e CS background which should make it easy to switch to SWE but may be harder to shift at FB as a DE :/

PearceN9714op·

I won’t lie, as a first job out of college this was a massive amount of money (moreso than some of the other jobs). I did have a Google SWE offer as well, but opted against it since I wanted a faster culture. But in hindsight, I wonder if I would have been better off with that.

PearceN9714op·

I think DS is truly interesting, even under a more analytics domain, there’s a lot of extremely interesting problems to tackle. ML is almost entirely a SWE driven venture (although I’ve seen some truly cool data science work around there). I believe I would be open to both right now over DE.

ANALOGquartz08·

DE work is consistently like that at FB, people get suckered in with the pay and its FB. Sucks even more that the RSU grants are less than SWE

PearceN9714op·

TC is 120k base, 40k signing, and 25k/year RSU (although, I’m getting close to that one year mark). There also a bonus that starts at 10% of base but is scaled to individual and org performance (so last half I got a 1.5x multiplier on the bonus).
I tend to think Data Engineer as a role has more potential but I do feel as though a lot of the tasks a data engineer could be doing are sort of consumed in SWE gig at Apple. I have a few guesses on why that might be, but I tend to think it is one of the contributing factors to our modest pulse scores more generally.

PearceN9714op·

It’s possible that there is more exciting stuff to gig on. There is one DE group in particular that has some potential with respect to what I’m interested in.
That being said, pulse scores for DEs across the company is pretty modest compared to other roles (just considering PE, DS, and SWE). One of the strongest determinants of that does seem to be dissatisfaction with gig. Now there are a lot of layers to that for sure, but based on the few people I’ve talked to, it does seem like the limited nature of DE gig plays a strong role.

granite_ocelot_6005·

Not a DE, but saw my DEs do same shit mate, very sad gig as it seemed. Mine are also constantly crazy overworked because they are are supporting 3 teams and had to invent some creative ways to automate themselves (build customisable dashboards) and negotiate difficult on support levels. One had now changed teams, hope she’s doing better there.

PearceN9714op·

That’s a different thing that I didn’t really get to mention In my original post. More often then not, we are put in a position where we have to support so plenty of different XFN partners. And as the number of XFN partners increase, so to does the maintenance gig. In essence, it really creates a situation where we can’t really even explore more exciting workstreams or branch out into other kinds of gig.

Goblin09247·

Damn.. I’m supposed to join as a DE in august in the product analytics group.

I’m doing some really interesting work in Google - building real data products along with sde’s both of us do similar gig.

Sad that DE gig sucks at FB. Though fb pays significantly more.

PearceN9714op·

That’s kind of the struggle I’m in. I think DE as a job can be so much more if you allow it to be (as it is in other companies). That means things like management being supportive and willing to fight for the impact for more development oriented gig. Building data products as you mentioned is something that is considered a major side task. And that’s a real shame since building a role around constructing analytical pipelines is really limiting, and quite frankly, not satisfying (at least in my eyes). Ideally, there should be separate lenses to view data engineers under. But alas, the comp here is quite decent, especially if I progress. So then it becomes a matter of, do I do this for the money or do I shoot for what I enjoy.

ANALOGquartz08·

That’s a sizable problem with management these days regarding DE works. They never see the lengthy term value or bottom line value, then they wonder why the DS always have issues....

brisk_snail_9762·

I see this as a common problem across most companies where data orgs are very matured and bulk of the time spent by Data or BI engineers/analysts is actually using those data tools created by SWEs for their day-to-day gig. I'm not an insider but AFAIK, most of the data tools at FB (and yes they are top notch!) like Scuba, Puma, Dataswarm & even the available-source query engines like Hive & Presto were built by SWEs and are extensively used by DEs. As OP mentioned, eventually it may get monotonous as irrespective of the context or product you're employed on, core technical work still remains the same i.e. building pipelines and dashboards. Also if number of XFN partners to support keeps on increasing and managers don't value involvement in building data tools as elevated-impact, there's little time left or even incentive to explore interesting work within or outside current project. I feel for folks with primarily SWE experience who end up in DE roles, real thrill lies in creating such data tools/products instead of just using them.
Having mentioned that, FB DE is one of the most sought after roles and pays really well. Outside of FANG, in most companies across various industry sectors
(banking/insurance/healthcare/retail/travel etc) most of the data orgs are quite siloed and there are armies of analysts/consultants who either do only reporting (tableau,microstrategy,looker) and have limited SQL knowledge, or part of DWH
crew who only are SQL monkeys & work only on loading data to DWH/data marts which will be used for reporting & other teams who work on building crappy internal frameworks and tools used by previous two categories. Not to mention layers of bureaucracy as well. I think FB's "full stack DE" is interesting role in a way where a DE fully owns the core dataset (from logging -- pipelines -- dashboards) of the product he/she works on and is closely involved with XFN partners. For folks who enjoy building pipelines and dashboards, FB is a great place to gig as a DE and make lot of money rather than doing the same somewhere else for peanuts!! :-D

super_vertex_9898·

Hey @Meta do you gig as a Data/Big Data Engineer.

brisk_snail_9762·

Yes

super_vertex_9898·

Can you explain regarding the data engineer role at Meta in general. Read at multiple places that data engineers at Meta gig on some very interesting projects (in the field of data eng)

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