Meta

Social media / advertising · Data Engineering interview

SQL is king. A 5-SQL + 5-Python phone bar, practical Python streaming, product-sense data modeling, and a decisive Ownership round.

Cloud / platform

Internal stack (Presto/Hive/Spark, Dataswarm) — not public cloud

Reported difficulty

Not reported

SQLPythonPrestoHiveData modelingProduct sense

Hiring process

Recruiter

Phone screen (5 SQL + 5 Python)

Onsite (3 full-stack)

Ownership round

Offer

Round-by-round breakdown

Phone screen

· Coderpad — pass = 3+ of eachHigh confidence

5 SQL questions
5 Python questions

SQL

High confidence

What % of Messenger users active yesterday made a video call?
Unique logins by a user on facebook.com
Multi-schema analytical queries; NULL handling

Python

High confidence

Stream of ride requests → count per 15-minute tumbling window
Function that dynamically formats a SQL query from parameters
Practical (not DSA) data manipulation

Data Modeling / Product Sense

High confidence

Brainstorm the data needs of a Meta product; design schemas
Design a dashboard for an aspect of user behavior
Rate the popularity of a posted video
Should Facebook change something in the newsfeed?

Ownership (Behavioral)

· 30 min standaloneHigh confidence

Own outcomes, navigate friction, extract impact from ambiguity
Problem → action → measurable change

System & pipeline design prompts

Product data modeling (events, profiles)
Metric/dashboard design under product sense

Prep — high priority

SQL: multi-schema analytical, %-of-users, NULL handling
Practical Python: tumbling windows, string/dict manipulation
Data modeling + product sense (metrics, dashboards)
Ownership STAR stories with measurable outcomes

Prep — medium priority

Distributed concepts
Meta product knowledge

Rejection patterns

Not clearing the 5+5 phone bar (need 3+ each)
Weak product sense
Vague Ownership stories without measurable impact
NULL/edge-case mistakes in SQL

Reported experiences

Data Engineer

2025First-hand

Phone (5 SQL + 5 Python) → onsite (3 full-stack SQL+Python+modeling/product + 1 Ownership). Real Qs: Messenger video-call %, unique logins, 15-min tumbling-window ride requests, dynamic SQL formatter, product-sense dashboards.

Rehearse for Meta

Answered questions on what Meta actually asks — each with the short answer, the answer that gets you rejected, and the follow-up.

Then build one and have it reviewed: design a daily orders pipeline or model a marketplace. No account.

All interview experiences

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Big Tech & Enterprise Software