Meta SQL interview questions
Product analytics at massive scale — engagement, retention and funnel metrics. Practice reconstructed Meta-style SQL, Python and pandas interview questions below — run and grade them instantly in your browser.
sqlpythonpandaseasy2medium6hard4
typical interview loop
- 1.Recruiter screen
- 2.Technical screen: 2–3 SQL questions in a shared editor (~45 min)
- 3.Onsite: SQL / Python coding, product-sense metrics case, behavioral
- › Expect follow-ups that change the metric definition mid-question.
- › Practice DAU/MAU, retention cohorts and anti-joins.
most-tested topics
LEFT JOIN
3
JOIN
2
GROUP BY
2
sorting
2
self join
2
DISTINCT
1
Based on 12 reconstructed Meta-style questions.
practice path
1 free · 11 Protype
level
- 1Active users who postedsqleasy
- 2Users who never postedsqleasy
- 3Engagement per postsqlmedium
- 4Friend suggestions via mutualspythonmedium
- 5Message delivery percentilespythonmedium
- 6Reels completion funnelsqlmedium
- 7Session windows from timestampspythonmedium
- 8Top posts by like countsqlmedium
- 9Friend suggestions by mutual friendssqlhard
- 10Last-click attribution windowpandashard
- 11Reciprocal engagementsqlhard
- 12Running total of new userssqlhard
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