Meta Data Engineer I interview questions

A standard recruiter chat followed by a 60-minute technical screen that felt like a total speed test - 25 minutes for SQL (window functions, self-joins) and then 25 minutes for Python (dictionaries, sets, and list manipulation). Its less about complex logic and more about how fast you can write clean code without an IDE to help you. Onsite was 4 rounds: three full stack sessions and one ownership behavioral round. Each full stack round is a 60-minute case study where you take a product scenario, like Instagram Reels or Marketplace, and drive it end-to-end. You define the KPIs (product sense), build out the schema (data modeling), and then write the actual SQL to fetch those metrics. The modeling part is where they really grill you the most and ask follow up ques - be ready to explain why you chose specific dimension types. The transition from a product goal to a technical schema is the hardest part. I did a few mocks on Prepfully specifically for these full stack rounds and it helped me get the timing down. I’d say know your Kimball fundamentals (SCDs, bridge tables) and be mindful of time

The interview process had 1 Online Technical Assessment with SQL and Python questions. Then I had 4 final rounds. 3 full-stack, which tested product sense, data modelling, ETL pipeline debug questions. 1 was ownership that revolved around Behavioural skills and Meta's core values