SQL Interview Mastery: 100 Questions Every Data Professional Must Know (2026 Edition): The Ultimate SQL Interview Guide for Data Analysts, Data Scientists, Software Engineers, Business Analysts, Data Engineers, and AI Professionals

Prof.(Dr.) D G Mahto, Founder & CEO -

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SQL Interview Mastery: 100 Questions Every Data Professional Must Know (2026 Edition)

The Ultimate SQL Interview Guide for Data Analysts, Data Scientists, Software Engineers, Business Analysts, Data Engineers, and AI Professionals

Introduction

Structured Query Language (SQL) remains one of the most valuable technical skills in today's data-driven world. Whether you're applying for a role as a Data Analyst, Data Engineer, Machine Learning Engineer, Business Intelligence Developer, Software Engineer, or Data Scientist, SQL is almost guaranteed to appear in the interview process.

Despite the rise of Artificial Intelligence, cloud computing, and big data technologies, organizations continue to rely on SQL to store, retrieve, analyze, and manage business-critical information.

Top employers such as Google, Microsoft, Amazon, Meta, Apple, Netflix, Uber, Airbnb, Oracle, Salesforce, JPMorgan Chase, and thousands of startups test SQL proficiency during technical interviews because it reflects a candidate's ability to work with real-world data.

This guide provides a structured roadmap to mastering SQL interview preparation, along with 100 essential SQL interview questions categorized by difficulty and topic.

Why SQL Is Still One of the Most In-Demand Skills

SQL is used in almost every industry:

  • Banking

  • Healthcare

  • Manufacturing

  • E-commerce

  • Education

  • Telecommunications

  • Government

  • Retail

  • Logistics

  • Artificial Intelligence

Professionals who understand SQL can efficiently analyze large datasets, build dashboards, automate reporting, and support data-driven decision-making.

Who Should Learn SQL?

SQL is essential for:

  • Data Analysts

  • Business Analysts

  • Data Engineers

  • Database Administrators

  • Machine Learning Engineers

  • AI Engineers

  • Software Developers

  • Backend Engineers

  • BI Developers

  • Product Analysts

Companies That Test SQL Interviews

Almost every major technology company evaluates SQL skills.

Examples include:

  • Google

  • Microsoft

  • Amazon

  • Meta

  • Apple

  • Netflix

  • Uber

  • Airbnb

  • Oracle

  • Adobe

  • Salesforce

  • Walmart Global Tech

  • Accenture

  • Deloitte

  • Infosys

  • TCS

  • Flipkart

  • PhonePe

SQL Interview Roadmap

A structured preparation plan helps build confidence.

Step 1

Master SQL Fundamentals

Learn:

  • Database concepts

  • Tables

  • Rows

  • Columns

  • Primary Keys

  • Foreign Keys

Step 2

Learn Querying

Practice:

  • SELECT

  • WHERE

  • ORDER BY

  • LIMIT

  • DISTINCT

Step 3

Master Filtering

Topics:

  • AND

  • OR

  • NOT

  • LIKE

  • BETWEEN

  • IN

  • EXISTS

Step 4

Aggregation

Study:

  • COUNT()

  • SUM()

  • AVG()

  • MIN()

  • MAX()

  • GROUP BY

  • HAVING

Step 5

Joins

Master:

  • INNER JOIN

  • LEFT JOIN

  • RIGHT JOIN

  • FULL JOIN

  • SELF JOIN

  • CROSS JOIN

Step 6

Subqueries

Understand:

  • Nested queries

  • Correlated subqueries

  • Scalar subqueries

Step 7

Window Functions

Essential topics:

  • ROW_NUMBER()

  • RANK()

  • DENSE_RANK()

  • LEAD()

  • LAG()

  • NTILE()

Step 8

Common Table Expressions (CTEs)

Practice:

  • WITH clause

  • Recursive CTEs

  • Multiple CTEs

Step 9

Optimization

Learn:

  • Indexes

  • Execution plans

  • Query optimization

  • Partitioning

  • Normalization

100 SQL Interview Questions

Basic SQL (1–20)

  1. What is SQL?

  2. Difference between SQL and MySQL?

  3. What is a database?

  4. What is a table?

  5. What is a primary key?

  6. What is a foreign key?

  7. What is NULL?

  8. What is DISTINCT?

  9. Difference between DELETE, DROP, and TRUNCATE?

  10. What is a constraint?

  11. Explain UNIQUE.

  12. What is NOT NULL?

  13. What is DEFAULT?

  14. Explain CHECK constraints.

  15. What is AUTO_INCREMENT?

  16. What is ORDER BY?

  17. What is LIMIT?

  18. What is WHERE?

  19. What is BETWEEN?

  20. Difference between CHAR and VARCHAR?

Intermediate SQL (21–50)

  1. Explain GROUP BY.

  2. What is HAVING?

  3. Difference between WHERE and HAVING?

  4. What is INNER JOIN?

  5. Explain LEFT JOIN.

  6. What is RIGHT JOIN?

  7. What is FULL OUTER JOIN?

  8. What is CROSS JOIN?

  9. Explain SELF JOIN.

  10. What is UNION?

  11. Difference between UNION and UNION ALL?

  12. What is a subquery?

  13. What is a correlated subquery?

  14. What is EXISTS?

  15. What is IN?

  16. Difference between ANY and ALL?

  17. What are aggregate functions?

  18. What is COALESCE()?

  19. Explain CASE statements.

  20. What is IFNULL() or ISNULL()?

  21. Difference between COUNT(*) and COUNT(column)?

  22. What is CAST()?

  23. Explain aliases.

  24. What is a view?

  25. What is a materialized view?

  26. Explain stored procedures.

  27. What are triggers?

  28. What are transactions?

  29. Explain COMMIT.

  30. Explain ROLLBACK.

Advanced SQL (51–80)

  1. What is ACID?

  2. Explain normalization.

  3. What are normal forms?

  4. Explain denormalization.

  5. What are indexes?

  6. Clustered vs. non-clustered indexes?

  7. Explain execution plans.

  8. What are CTEs?

  9. Recursive CTE?

  10. Window functions?

  11. ROW_NUMBER()

  12. RANK()

  13. DENSE_RANK()

  14. LEAD()

  15. LAG()

  16. NTILE()

  17. Explain PARTITION BY.

  18. What are temporary tables?

  19. Explain pivoting.

  20. What is unpivoting?

  21. Explain MERGE.

  22. What is dynamic SQL?

  23. Explain recursive queries.

  24. What are database locks?

  25. Deadlocks?

  26. Isolation levels?

  27. Explain optimistic locking.

  28. Explain pessimistic locking.

  29. Database sharding?

  30. Database partitioning?

Scenario-Based SQL (81–100)

  1. Find the second-highest salary.

  2. Find duplicate records.

  3. Remove duplicates.

  4. Calculate running totals.

  5. Find top three salaries per department.

  6. Find employees hired in the last six months.

  7. Find customers with no orders.

  8. Rank products by revenue.

  9. Identify inactive users.

  10. Find consecutive login days.

  11. Detect missing sequence numbers.

  12. Calculate month-over-month growth.

  13. Find the most frequently purchased product.

  14. Calculate customer lifetime value.

  15. Build a sales leaderboard.

  16. Identify churned customers.

  17. Calculate rolling averages.

  18. Write an employee hierarchy query.

  19. Optimize a slow query.

  20. Design a reporting database.

Practical SQL Problems to Solve Daily

Strengthen your skills by practicing:

  • Employee Management

  • Banking Database

  • E-commerce Platform

  • Hospital Management

  • University Records

  • Airline Reservation

  • Sales Analytics

  • Retail Inventory

  • Movie Ratings

  • Online Learning Platform

SQL Topics Frequently Asked in Interviews

Database Design

  • ER Diagrams

  • Keys

  • Relationships

  • Constraints

Query Writing

  • Filtering

  • Sorting

  • Aggregation

  • Joins

  • Nested Queries

Performance Optimization

  • Indexes

  • Execution Plans

  • Partitioning

  • Query Tuning

Advanced SQL

  • Window Functions

  • Recursive Queries

  • CTEs

  • Transactions

SQL Interview Tips

  • Read each question carefully before writing a query.

  • Practice on real datasets.

  • Optimize queries after they work correctly.

  • Explain your thought process during interviews.

  • Consider edge cases such as NULL values and duplicate records.

  • Review execution plans for complex queries.

Recommended Practice Platforms

  • LeetCode

  • HackerRank

  • StrataScratch

  • DataLemur

  • SQLBolt

  • Mode SQL Tutorial

Work on timed challenges to simulate interview conditions.

30-Day SQL Preparation Plan

Week 1

  • SQL Basics

  • SELECT

  • WHERE

  • ORDER BY

  • Filtering

Week 2

  • Joins

  • GROUP BY

  • HAVING

  • Subqueries

Week 3

  • Window Functions

  • CTEs

  • Transactions

  • Views

Week 4

  • Optimization

  • Mock Interviews

  • Scenario-Based Problems

  • Timed Practice

Common Mistakes to Avoid

  • Ignoring NULL handling

  • Using unnecessary subqueries

  • Forgetting GROUP BY requirements

  • Choosing incorrect JOIN types

  • Neglecting performance considerations

  • Not testing queries with edge cases

Final Checklist Before Your SQL Interview

  • SQL syntax fundamentals

  • Joins

  • Aggregations

  • Window functions

  • CTEs

  • Transactions

  • Indexes

  • Query optimization

  • Scenario-based questions

  • Timed practice

Final Thoughts

SQL continues to be one of the most valuable and enduring technical skills for data professionals. Whether you're preparing for your first job or advancing into senior data roles, strong SQL proficiency can significantly improve your interview performance and career prospects.

Success comes from consistent practice rather than memorization. Build queries from scratch, analyze execution plans, solve real business problems, and revisit difficult concepts until they become second nature. Focus on understanding why a query works, not just how to write it.

By mastering the topics covered in this guide and practicing the 100 interview questions regularly, you'll be well-prepared to tackle SQL interviews with confidence and demonstrate the analytical thinking employers seek.

Key Takeaways

  • Master SQL fundamentals before advanced topics.

  • Practice joins, aggregations, subqueries, and window functions extensively.

  • Learn query optimization and indexing concepts.

  • Solve real-world business scenarios regularly.

  • Practice under time constraints to simulate interviews.

  • Explain your reasoning clearly during technical interviews.

Your SQL Success Formula

SQL Fundamentals + Daily Practice + Real-World Scenarios + Query Optimization + Mock Interviews = High-Confidence Data Professional

Master SQL today, and you'll build a foundation that supports careers in analytics, software engineering, artificial intelligence, cloud computing, and data engineering.

Prof. (Dr.) D. G. Mahto **Visionary Director | Professor | Leader | Educator | Mentor** With over 25 years of distinguished academic and leadership excellence, **Prof. Mahto** is a dynamic Director, Professor, philanthropist, HEI builder, author, consultant, reviewer, and career strategist. Through his flagship initiative, *“Career Education for Success — Discover, Apply, Succeed!”*, he has empowered individuals, institutions, & professional communities by blending knowledge, innovation, & mentorship. He holds a Ph.D. in Engineering from NIT Jamshedpur and has further strengthened his academic portfolio through Post-Doctoral Programs at premier institutions including IITs, NITs, & IIIT s. His accomplishments can be viewed on "https://www.linkedin.com/in/prof-dr-dalgobind-mahto-ba589b35b?utm_source=share_via&utm_content=profile&utm_medium=member_android

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