Meta data interview guide
Product analytics at massive scale — engagement, retention and funnel metrics.
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
DISTINCT
1
dicts
1
sets
1
Based on 8 reconstructed Meta-style questions.
practice path
1 free · 7 Pro- 1Active users who postedsqlEasy
- 2Engagement per postsqlMedium
- 3Friend suggestions via mutualspythonMedium
- 4Reciprocal engagementsqlHard
- 5Running total of new userssqlHard
- 6Session windows from timestampspythonMedium
- 7Top posts by like countsqlMedium
- 8Users who never postedsqlEasy
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