Data Manipulation (SQL/Python) Interview Questions
Practice 653 real Data Manipulation (SQL/Python) interview questions for 2026. Covers companies like Meta, Amazon, TikTok, DoorDash, and Capital One. Real questions from actual interviews with detailed solutions — designed for focused interview preparation for data analysts, data scientists, and data engineers who must move fluidly between SQL and Python during live screens and take-home tasks. These questions emphasize practical skills: writing correct, efficient SQL (joins, GROUP BY, window functions, CTEs, NULL handling, and performance-aware predicates) and idiomatic Python/Pandas solutions (vectorized transforms, merges, reshaping, datetime handling, and robust data-cleaning). Interviewers evaluate correctness, edge-case reasoning, runtime and memory tradeoffs, reproducibility, and clear communication of assumptions. Expect timed whiteboard-style queries, pair-programming in a shared editor, and take-home notebooks. To prepare, practice translating SQL ↔ Pandas, explain results aloud, time-box exercises, test edge cases, and review common pitfalls such as NULL semantics, grouping logic, off-by-one errors, and inefficient joins.
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Count words in a document robustly
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Compute ad revenue metrics by geography in SQL
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You are given the following interview tasks. Write solutions in SQL and/or Python (pandas) as appropriate. Task 1 — Second highest salary You have a t...