Practice the exact SQL patterns Meta asks in data analyst and data engineer interviews. Window functions, aggregations, date functions — with AI tutoring and instant feedback.
Based on analysis of hundreds of Meta interview reports. These are the topic weights you should prepare for.
40%
Window Functions
RANK, ROW_NUMBER, LAG/LEAD, percentiles, running totals, moving averages
25%
Aggregation & GROUP BY
HAVING, conditional aggregates, ratios, COUNT DISTINCT, filtered sums
20%
JOINs & Subqueries
Self-joins, anti-joins, CTEs, correlated subqueries, EXISTS/NOT EXISTS
15%
Date & String Functions
DATE_TRUNC, EXTRACT, interval math, CONCAT, string parsing
These are the types of questions Meta asks in their 45-minute SQL screen. Practice all of them inside SQL Quest.
Calculate the rolling 7-day average of daily active users
Find users who were active in both the current and previous month
Rank departments by average salary, including ties
Calculate month-over-month growth rate for each product
Find the percentage of users who completed onboarding
Identify users whose activity dropped more than 50% week-over-week
45-minute screen with 2-3 SQL questions of increasing difficulty. You write queries live in CoderPad or a shared editor. The interviewer watches your approach in real time — not just the final answer.
Correct logic and complete results. Edge case handling (NULLs, empty groups, ties). Query optimization awareness — can you explain why one approach is faster? Clear communication of your thought process.
Practice window functions heavily — they appear in 40% of Meta questions. Use real datasets, not toy examples. Time yourself at 15 minutes per question. Talk through your approach out loud while writing.
Practice 50+ Meta-style SQL questions with AI tutoring, instant feedback, and real datasets. No signup required.
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