Data Science SQL Interview Questions

High-frequency topics include SELECT, WHERE, JOINs, GROUP BY, HAVING, and simple aggregation logic. These questions are foundational because they reveal whether you can move from raw data to a metric correctly.

A strong answer often begins by clarifying the data model or key assumptions before you write the query.

• Join choice and how row counts change.
• Aggregation logic and metric definition.
• Filtering, grouping, and post-aggregation conditions.
• Subqueries and CTEs for clearer structure.

More advanced SQL interviews often use ranking, running totals, cohort analysis, first-value logic, or de-duplication scenarios. Window functions are especially useful because they show whether you can reason about partitions and ordering without collapsing the dataset too early.

A common interview prompt asks for each customer’s most recent order, or for ranking users within a segment. That is a good place to use a window function instead of a more fragile join pattern.

WITH ranked_orders AS (
  SELECT
    customer_id,
    order_id,
    order_date,
    ROW_NUMBER() OVER (
      PARTITION BY customer_id
      ORDER BY order_date DESC
    ) AS rn
  FROM orders
)
SELECT customer_id, order_id, order_date
FROM ranked_orders
WHERE rn = 1;

Say the metric, the grain of the data, and the edge cases before you write much SQL. That is often what separates stronger candidates from people who can only type queries quickly.

After the query, explain how you would validate the output and what would break it.

The same topic should not sound identical in every interview. A recruiter usually needs a clear and concise answer. A hiring manager needs more evidence. A final-round interviewer often tests judgment, consistency, and fit.

Before you practice, decide which stage you are preparing for. Then adjust the amount of detail, the example you choose, and the way you close the answer.

Good interview preparation is not just reading sample answers. It is a repeatable loop that turns an idea into a spoken answer you can deliver under pressure.

Use this checklist after you practice. If an answer fails more than two items, revise it before you use it in a real interview.

• The first sentence directly answers the question.
• The example includes context, action, and result instead of only responsibilities.
• The answer has at least one concrete detail: a metric, tool, customer, patient, stakeholder, deadline, or constraint.
• The story makes your judgment visible, not just your activity.
• The ending connects back to the role, company, team, or interview stage.
• You can handle at least two follow-up questions without changing the story.

• Writing SQL before clarifying the metric definition.
• Using joins without thinking about duplicates or dropped rows.
• Avoiding window functions when they fit the problem well.
• Ignoring query performance or validation entirely.

After the first answer, ask for one critique on structure, one critique on evidence, and one follow-up question that a real interviewer might ask. Then answer again using the same story with tighter wording.

Use the linked guides below to build a tighter interview-prep cluster around this topic and strengthen your role-specific practice.