A practical SQL question bank for hiring data analysts — joins, aggregation, window functions, and the analytical judgement that separates someone who writes queries from someone who answers questions with data.
For a data analyst, SQL is the instrument, not the job. The job is turning a vague business question into a precise query and then into an answer someone can act on. So while you do need to confirm a candidate can write correct joins and aggregations, the more valuable signal is whether they think analytically: do they ask what the question really means, notice when a result looks wrong, and understand the difference between "the query ran" and "the answer is right"? The questions below build from core SQL mechanics up to applied scenarios. Use the early ones to confirm fluency — a strong analyst should explain the difference between an INNER and LEFT JOIN without hesitation — and the later ones to see how they handle ambiguity and messy data. Many real analytics bugs come from quietly dropped rows, double-counted joins, or NULLs behaving unexpectedly, so reward candidates who mention those risks unprompted. A practical exercise against a sample schema, paired with two or three of these discussion questions, gives a clear read on whether someone can be trusted with the numbers the business decides on.
Confirm fluency with two or three Core SQL questions, then spend most of the interview on the Applied Scenarios — ideally against a small sample schema the candidate can query live. The strongest signal is an analyst who validates their own results and flags where the data could mislead, not just one who returns a syntactically correct query.
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