Meta Data Engineering Manager reviews

3.2

36% would recommend to a friend

(476 total reviews)
avatar

Mark Zuckerberg

23% approve of CEO

33% positive business outlook

Data Engineering Manager employees have rated Meta with 3.2 out of 5 stars, based on 476 company reviews on Glassdoor. This indicates that most Data Engineering Manager professionals have a good working experience there. Meta is rated in line with the average (within 1 standard deviation) by Data Engineering Manager professionals compared to other employers within the Information Technology industry (3.7 stars).

Reviews by job title

476 reviews
3.0
Mar 3, 2026
Recommend
CEO approval
Business Outlook

Pros

Access to state-of-the-art tooling/resources and methodologies to test new technologies before they're broadly accessible to the field. Extremely smart coworkers, great facilities, fantastic benefits and pay. Meta branding can add to the resume if you're on a team with real impact.

Cons

Review culture is horrible. Performance pressure is constant, and expectations can be crushing depending on the team you join. Success here is highly political, you need a good manager and good relationships with higher-ups in your org. Post-2022, everyone is scared of being laid off and the anxiety + depression is toxic and contagious. There's high churn, and there's a lot of performative signaling to gain favor and stay in the game longer. Depending on your team, you may not work on anything interesting or high-impact. Take a job here if you're willing to work hard for a few months/years, but don't let your lifestyle creep up too much from the pay bump -- save aggressively in case of long-term unemployment if a re-org impacts you.

5.0
Feb 8, 2026
Recommend
CEO approval
Business Outlook

Pros

very rigourous and extremely good projects

Cons

no problem with the unnovation

2.0
Jan 27, 2026
Recommend
CEO approval
Business Outlook

Pros

The data platform is exceptionally robust, significantly enhancing developer velocity by abstracting away infrastructure complexities. The platform team has delivered a comprehensive ecosystem where the core pillars of data engineering—compute, storage, quality, and discovery—are seamlessly integrated. Their intentional design has drastically reduced operational overhead, allowing the engineering team to focus entirely on delivering high-impact data products.

Cons

The primary challenge was the disconnect between strategic mandates—like the top-down AI push—and the operational capacity of the data teams. In nascent product areas, the '0 to 1' build phase was frequently disrupted by changing requirements, leading to high team burnout. I believe that for AI innovation to succeed, there needs to be a distinction in how we resource matured data products versus new initiatives. Without a stabilized foundation, teams in the '0 to 1' phase are forced into a dual-track execution that risks both delivery quality and infrastructure health.

Viewing 58 - 60 of 476 Reviews

Glassdoor has 24,421 Meta reviews submitted anonymously by Meta employees. Read employee reviews and ratings on Glassdoor to decide if Meta is right for you.