Lilly Tech Systems
SQL Coding Challenges
Real SQL problems from data engineering and ML engineer interviews. Every challenge includes a schema setup, problem statement, and complete SQL solution with performance analysis. Master the SQL patterns that interviewers actually test.
Your Learning Path
Follow these lessons in order to build strong SQL skills for data and ML engineering interviews, or jump to any topic you need to practice.
1. SQL for Data/ML Interviews
What to expect in SQL interviews, dialect differences, common patterns, and a systematic approach to solving SQL problems under pressure.
2. Basic Queries & Aggregation
6 challenges: filtering, GROUP BY, HAVING, subqueries, CASE WHEN, COALESCE — the foundation every SQL interview builds on.
3. Joins & Subqueries
6 challenges: inner/left/self joins, correlated subqueries, EXISTS, anti-join patterns — the most tested SQL topic in interviews.
4. Window Functions
6 challenges: ROW_NUMBER, RANK, DENSE_RANK, LAG, LEAD, running totals, moving averages — the skill that separates senior from junior candidates.
5. CTEs & Recursive Queries
5 challenges: WITH clause, recursive CTE, hierarchical data, date generation, running calculations — elegant solutions to complex problems.
6. Advanced SQL Patterns
5 challenges: gaps and islands, pivot/unpivot, sessionization, funnel analysis, cohort retention — the problems that stump most candidates.
7. Query Optimization
5 challenges: EXPLAIN plans, indexing strategies, query rewriting, avoiding N+1, partitioning — critical for production data pipelines.
8. Patterns & Tips
SQL pattern cheat sheet, interview tips, FAQ accordion, and a reference of the most common SQL anti-patterns to avoid in interviews.
What You'll Learn
By the end of this course, you will be able to:
Solve SQL Interview Problems
Master joins, window functions, CTEs, and advanced patterns using the exact SQL idioms that interviewers expect to see.
Write Production-Quality SQL
Use proper indexing, optimize query plans, and write maintainable SQL that scales to billions of rows in real data pipelines.
Ace Data Engineering Interviews
Confidently handle the 33+ most common SQL problems asked at Google, Meta, Amazon, and data-focused companies.
Think in Sets, Not Loops
Develop the set-based thinking that makes complex SQL problems feel natural — the key mental shift interviewers look for.