SQL

Filtering and sorting, join types and their semantics, aggregation with GROUP BY, window functions for running totals and rankings, CTEs for readable query composition, DML for modifying data, schema and index design, and reading query execution plans to diagnose slow queries.

WHERE vs HAVING, INNER/LEFT/RIGHT/FULL/CROSS joins, NULL handling, GROUP BY mechanics, COUNT/SUM/AVG/MIN/MAX, OVER() clause, PARTITION BY, ROW_NUMBER/RANK/DENSE_RANK, LAG/LEAD, WITH (CTE), subquery vs CTE vs join, INSERT/UPDATE/DELETE, primary and foreign keys, B-tree indexes, covering indexes, EXPLAIN / EXPLAIN ANALYZE.

SQL is the single most-tested skill in data-adjacent interviews. Strong SQL fluency lets you answer business questions directly from the database without loading data into Python first — faster to explore, easier to share, and often far more efficient. Window Functions alone unlock an entire class of analytics patterns that would otherwise require multiple passes.

SQL interviews test your ability to think in sets rather than loops, choose the right join, use window functions for ranking and running totals, write readable multi-step queries with CTEs, and reason about performance. The progression from basic SELECT to window functions to query tuning maps almost exactly to junior → mid → senior expectations.