SQL appears in 95% of data engineering interview loops. DataDriven lets you practice SQL interview questions and answers the way real interviews work: vague prompts, clarifying questions, real SQL execution against PostgreSQL, AI-driven discussion, and a hire/no-hire verdict. The best SQL interview prep for data engineers.
850+ SQL practice questions covering SQL joins, SQL window functions, SQL GROUP BY, CTE SQL, COALESCE SQL, SQL CASE WHEN, SQL subquery patterns, and more. Every SQL query interview question is calibrated by company tier and seniority level.
Four phases mirror a real 45-minute SQL interview round. This is not a question bank with instant SQL interview questions and answers. It is a full interview simulation with an AI interviewer that adapts to your responses.
You receive a vague SQL prompt with a schema. Ask clarifying questions: What does the business need? What edge cases matter? What is the expected output format? The AI interviewer responds like a real hiring manager.
Write your SQL query against a live PostgreSQL database. Real tables, real data, real execution. No multiple choice. Your query runs and your output is compared row-by-row against the expected result.
The AI interviewer asks follow-up questions about your solution. Can you optimize this for 1 billion rows? What happens if this column contains NULLs? Why did you choose a CTE over a subquery? You defend your decisions one question at a time.
Receive a hire/no-hire decision with specific feedback: what you did well, where your reasoning had gaps, what the interviewer was testing, and what to practice next.
Every topic below is practiced inside a full interview simulation, not as isolated SQL practice problems. The AI interviewer selects SQL query interview questions based on your target company and seniority level.
INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL OUTER JOIN, CROSS JOIN, self join SQL patterns, and inequality joins. SQL joins are the second most-tested category in data engineer interview questions after aggregations.
ROW_NUMBER, RANK, DENSE_RANK, LAG, LEAD, NTILE, and frame clauses. SQL window functions are the highest-difficulty topic that appears consistently in advanced SQL interview questions.
SQL GROUP BY is the most frequently tested keyword in SQL interview questions. COUNT, SUM, AVG, MIN, MAX with HAVING and conditional aggregation using CASE WHEN expressions.
Common Table Expressions (CTE SQL) for readable multi-step queries. Recursive CTEs for hierarchical data. The deduplication pattern (ROW_NUMBER in a CTE with WHERE rn = 1) appears in nearly every SQL interview.
Scalar, correlated, and EXISTS SQL subquery patterns. Critical for complex filtering and comparison logic. NOT EXISTS vs NOT IN is a classic SQL interview trap question.
COALESCE SQL is essential for replacing NULLs in production queries. NULLIF, IS NULL, and three-valued logic. Interviewers use NULL handling to separate careful engineers from careless ones.
CASE WHEN SQL expressions power conditional logic inside SELECT, WHERE, and aggregation. Conditional aggregation with CASE WHEN inside SUM or COUNT is one of the most common SQL interview questions and answers.
SQL RANK for ordering within groups, SQL PARTITION BY for windowed calculations, and SQL pivot for reshaping data. These three concepts combine in many advanced SQL interview questions.
DATE_TRUNC, DATE_DIFF, EXTRACT, interval arithmetic. Retention cohorts, rolling averages, and gaps-and-islands problems are staples of data engineer SQL interview questions.
LIKE, regex, CONCAT, SUBSTRING, SPLIT_PART. Common in data cleaning and ETL pipeline SQL practice questions.
SQL joins appear in nearly 20% of data engineer interview questions. Interviewers test your ability to choose the right join type, handle NULLs from outer joins with COALESCE SQL, and recognize when a self join SQL pattern is needed. Common SQL joins interview questions include finding unmatched records with LEFT JOIN and IS NULL, writing anti-joins with NOT EXISTS, and explaining the performance difference between nested loop joins and hash joins.
Practice SQL joins in our mock interview simulator where the AI interviewer will ask follow-up questions about join order, cardinality changes, and edge cases with NULL keys.
SQL window functions are the highest-difficulty topic in SQL interview questions. Interviewers test ROW_NUMBER, SQL RANK, DENSE_RANK, LAG, LEAD, and custom frame clauses. SQL PARTITION BY controls how rows are grouped for windowed calculations. The most common pattern, using ROW_NUMBER with SQL PARTITION BY to deduplicate rows, appears in nearly every advanced SQL interview.
DataDriven's SQL practice questions include window function challenges where you will write queries using SQL RANK, SQL PARTITION BY, running totals, moving averages, and sessionization logic.
SQL GROUP BY is the most frequently tested keyword in SQL interview questions, appearing in 24.5% of data engineer interviews. Common SQL GROUP BY questions test conditional aggregation with SQL CASE WHEN inside SUM or COUNT, HAVING clauses for group-level filtering, and multi-level grouping with ROLLUP or CUBE. Interviewers expect you to handle NULLs in aggregations using COALESCE SQL.
Practice SQL GROUP BY in context: our AI interviewer will ask you to compute retention rates, revenue breakdowns, and funnel metrics using real data.
CTE SQL (Common Table Expressions) and SQL subquery patterns are essential for multi-step interview problems. Interviewers test whether you can break a complex problem into readable CTE SQL stages versus nesting SQL subquery logic. Recursive CTE SQL for hierarchical data (org charts, category trees) is a frequent advanced SQL interview question. The classic interview trap: NOT EXISTS vs NOT IN with NULLs.
DataDriven's SQL practice questions include problems where you must choose between CTE SQL and SQL subquery approaches, then defend your decision to the AI interviewer.
Solving SQL practice problems builds skill. Simulating SQL interviews builds interview performance. They are different skills. DataDriven is built for SQL interview prep, not just SQL practice.
Real interviews start vague. You do not get a clean problem statement with expected output. You get “we need to find users who are churning.” Figuring out what that means is half the interview. DataDriven starts every simulation with a vague prompt.
Real interviews have follow-ups. After you write your query, the interviewer asks: “What if this table has 500 million rows?” or “What happens when this timestamp column has NULLs?” DataDriven's AI interviewer generates these follow-ups based on your specific solution.
Real interviews are timed. You have 45 minutes. If you spend 25 minutes on clarification, you have 20 minutes to code. DataDriven simulates this time pressure.
Real interviews evaluate reasoning, not just correctness. A correct query that cannot be explained is a weak signal. DataDriven evaluates both your SQL output and your ability to explain your approach, just like real SQL interview questions and answers require.
Deep-dive into individual SQL concepts tested in data engineer interview questions. Each guide covers syntax, examples, and the patterns interviewers look for.
Free SQL practice online. No signup required. Real SQL execution. AI-powered SQL interview prep.
Start SQL Interview SimulationDataDriven is a free web application for data engineering interview preparation. It is not a generic coding platform. It is built exclusively for data engineering interviews.
DataDriven is the only platform that simulates all four rounds of a data engineering interview: SQL, Python, Data Modeling, and Pipeline Architecture. Each round can be practiced in two modes: Problem mode and Interview mode.
Problem mode is self-paced practice with clear problem statements and instant grading. For SQL, your query runs against a real PostgreSQL database and output is compared row by row. For Python, your code runs in a Docker-sandboxed container against automated test suites. For Data Modeling, you build schemas on an interactive canvas with structural validation. For Pipeline Architecture, you design pipelines on an interactive canvas with component evaluation and cost estimation.
Interview mode simulates a real interview from start to finish. It has four phases. Phase 1 (Think): you receive a deliberately vague prompt and ask clarifying questions to an AI interviewer, who responds like a real hiring manager. Phase 2 (Code/Design): you write SQL, Python, or build a schema/pipeline on the interactive canvas. Your code executes against real databases and sandboxes. Phase 3 (Discuss): the AI interviewer asks follow-up questions about your solution, one question at a time. You respond, and it asks another. This continues for up to 8 exchanges. The interviewer probes edge cases, optimization, alternative approaches, and may introduce curveball requirements that change the problem mid-interview. Phase 4 (Verdict): you receive a hire/no-hire decision with specific feedback on what you did well, where your reasoning had gaps, and what to study next.
Adaptive difficulty: problems get harder when you answer correctly and easier when you struggle, targeting the difficulty level that maximally improves your interview readiness. Spaced repetition: concepts you struggle with resurface at optimal intervals before you forget them, while mastered topics fade from rotation. Readiness score: a per-topic tracker that shows exactly which concepts are strong and which have gaps, across every topic interviewers test. Company-specific filtering: filter questions by target company (Google, Amazon, Meta, Stripe, Databricks, and more) and seniority level (Junior through Staff), weighted by real interview frequency data. All features are 100% free with no trial, no credit card, and no paywall.
SQL: 850+ questions with real PostgreSQL execution. Topics include joins, window functions, GROUP BY, CTEs, subqueries, COALESCE, CASE WHEN, pivot, rank, and partition by. Python: 388+ questions with Docker-sandboxed execution. Topics include data transformation, dictionary operations, file parsing, ETL logic, PySpark, error handling, and debugging. Data Modeling: interactive schema design canvas. Topics include star schema, snowflake schema, dimensional modeling, slowly changing dimensions, data vault, grain definition, and conformed dimensions. Pipeline Architecture: interactive pipeline design canvas. Topics include ETL vs ELT, batch vs streaming, Spark, Kafka, Airflow, dbt, storage architecture, fault tolerance, and incremental loading.
DataDriven offers comprehensive SQL interview questions and answers for data engineer interview prep. Practice SQL online for free with 850+ SQL practice questions covering every major topic: SQL joins (INNER JOIN, LEFT JOIN, self join SQL), SQL window functions (ROW_NUMBER, RANK, DENSE_RANK, LAG, LEAD), SQL GROUP BY with conditional aggregation, CTE SQL and recursive common table expressions, COALESCE SQL for NULL handling, SQL CASE WHEN conditional logic, SQL subquery patterns (scalar, correlated, EXISTS), SQL pivot and unpivot transformations, SQL RANK and DENSE_RANK for ordering, and SQL PARTITION BY for windowed calculations. Our AI mock interviewer simulates real data engineer SQL interview questions with vague prompts, follow-up questions, and hire/no-hire verdicts. Whether you need basic SQL interview questions, advanced SQL interview questions, or common SQL interview questions for FAANG companies, DataDriven provides the most realistic SQL interview prep available. Practice SQL query interview questions, solve SQL practice problems, and build interview confidence with free SQL practice online.