SQL Interview Questions for Data Scientists (2026)

Quick Answer: What Actually Gets Asked

What Interviewers Are Actually Testing

Nobody hiring a data scientist actually cares whether a candidate has a JOIN syntax memorized — a reference is one search away on the job. What interviewers are evaluating is whether a candidate can take an ambiguous business question, translate it into a structured query, and reason clearly about tradeoffs — including performance, which recent interview trends weight more heavily than they used to, alongside live, timed coding rather than take-home problems.

That reframing changes how to prepare. Memorizing 60 answers verbatim is a weak strategy, because interviewers routinely follow up with "why did you choose that join" or "how would this behave on a 10-million-row table" — questions a memorized answer doesn't survive. Understanding the pattern behind each question, and being able to explain the reasoning out loud, is what actually transfers to a live interview.

Beginner: Fundamentals Check

These confirm a candidate has the core toolkit solid before anything more complex gets asked.

SELECT MAX(salary) AS second_highest
FROM employees
WHERE salary < (SELECT MAX(salary) FROM employees);

SELECT email, COUNT(*) AS occurrences
FROM customers
GROUP BY email
HAVING COUNT(*) > 1;

Intermediate: Joins & Window Functions

This tier tests whether a candidate can handle multi-table logic and the ranking/comparison patterns that show up in almost every real analytics task.

WITH ranked AS (
  SELECT name, department, salary,
    ROW_NUMBER() OVER (PARTITION BY department ORDER BY salary DESC) AS rn
  FROM employees
)
SELECT name, department, salary
FROM ranked
WHERE rn <= 3;

SELECT e.name AS employee, m.name AS manager
FROM employees e
JOIN employees m ON e.manager_id = m.employee_id
WHERE e.salary > m.salary;

Advanced: Optimization & Design

This is the tier that's grown the most in emphasis recently — interviewers increasingly care as much about how a query would perform at scale as whether it's correct.

SELECT order_date, daily_revenue,
  SUM(daily_revenue) OVER (
    ORDER BY order_date ROWS BETWEEN 6 PRECEDING AND CURRENT ROW
  ) AS rolling_7day
FROM daily_revenue_summary;

How to Prepare: A Practical Sequence

Mistakes That Give Away a Beginner

• Jumping straight to code without asking a clarifying question. Real interview questions are often deliberately ambiguous — asking "does this need to include cancelled orders?" is itself a signal of good judgment.
• Reciting a memorized definition instead of reasoning through the specific scenario. Interviewers routinely follow up with a twist on the original question specifically to check for this.
• Never mentioning performance on a question involving a large or unspecified table size — a missed opportunity to demonstrate production awareness.
• Going silent while writing the query. In a live round, narrating your thinking is often weighted as much as the final answer.
• Not testing the query against edge cases out loud — an empty table, NULLs, ties — even mentioning "I'd also check how this handles ties" is a strong closing signal.

Frequently Asked Questions

Conclusion: Patterns Over Memorization

Every question in this guide maps back to a specific mistake or trap covered somewhere earlier in this cluster — NULL handling, join fan-out, the GROUP BY column rule, sargability, gaps-and-islands. That's not a coincidence; interview questions are, almost by design, the moments where those exact misunderstandings surface fastest. Prepare by understanding why each pattern exists, not by memorizing 60 disconnected answers, and practice narrating your reasoning out loud — that's the actual skill being evaluated in a live round.

Work through the 18 questions above until you can write each one without hesitation, then move to the next article in this cluster, which compares the major database platforms you'll likely be asked to work with on the job.