TikTok
Medium
Data ScientistWrite SQL for last-7-day metrics without windows
Data Manipulation (SQL/Python)
0
0
October 13, 2025
SQL JOIN Interview Questions
SQL JOIN questions test whether you can combine data across tables while preserving the right grain and relationships. Expect INNER, LEFT, RIGHT, CROSS, and FULL OUTER JOINs, plus multi-table joins and JOIN + aggregation patterns.
171Questions
45Companies
Common SQL JOIN interview patterns
- INNER vs LEFT JOIN logic
- Anti-joins (find missing records)
- Self-joins for comparisons within a table
- JOIN + GROUP BY for aggregated results
- Conditional joins with additional predicates
- Multi-key joins across composite keys
- Deduplication using JOINs
SQL JOIN interview questions
Filter and sort
Boston Consulting Group
Medium
Data ScientistTransform and aggregate messy event data
Data Manipulation (SQL/Python)
0
0
October 13, 2025
Meta
Medium
Data ScientistWrite SQL for social feed metrics and ties
Data Manipulation (SQL/Python)
0
0
October 13, 2025
DoorDash
Medium
Data ScientistWrite SQL to backtest refund policy
Data Manipulation (SQL/Python)
0
0
October 13, 2025
Pinterest
Medium
Data ScientistWrite SQL to rank categories by impressions
Data Manipulation (SQL/Python)
0
0
October 13, 2025
Roblox
Medium
Data ScientistCompute ARPDAU/ARPPU by country
Data Manipulation (SQL/Python)
0
0
October 13, 2025
Roblox
Medium
Data ScientistWrite SQL to flag suspect payments and chargebacks
Data Manipulation (SQL/Python)
0
0
October 13, 2025
Capital One
Medium
Data ScientistWrite one SQL for exam scores aggregation
Data Manipulation (SQL/Python)
0
0
October 13, 2025
Intuit
Medium
Data ScientistCompute paid subscriber YoY counts by month
Data Manipulation (SQL/Python)
0
0
October 13, 2025
Upstart
Medium
Data ScientistSolve SQL CTR and Python analytics tasks
Data Manipulation (SQL/Python)
0
0
October 13, 2025
Pinterest
Medium
Data ScientistCompute CTR by pin_format for new US users
Data Manipulation (SQL/Python)
0
0
October 13, 2025
Freddie Mac
Medium
Data ScientistDesign SQL cleaning, mapping, dedupe, and keying
Data Manipulation (SQL/Python)
0
0
October 13, 2025
Twitch
Medium
Data ScientistSolve advanced SQL for streaming analytics
Data Manipulation (SQL/Python)
0
0
October 13, 2025
Capital One
Medium
Data ScientistMerge ad CSVs and compute CTR
Data Manipulation (SQL/Python)
0
0
October 13, 2025
Capital One
Medium
Data ScientistAggregate exam scores with NULL handling
Data Manipulation (SQL/Python)
0
0
October 13, 2025
Meta
Medium
Data ScientistCompute feed ad frequency and retention in SQL
Data Manipulation (SQL/Python)
0
0
October 13, 2025
Intuit
Medium
Data ScientistExclude free subscribers via anti-join
Data Manipulation (SQL/Python)
0
0
October 13, 2025
Intuit
Medium
Data ScientistCompute monthly new subscribers and YoY deltas
Data Manipulation (SQL/Python)
0
0
October 13, 2025
Meta
Medium
Data ScientistCompute 7-day views and reactions by relationship
Data Manipulation (SQL/Python)
0
0
October 13, 2025
Freddie Mac
Medium
Data ScientistAssess SQL cleaning, mapping, joins, keys, and DDL/DML
Data Manipulation (SQL/Python)
0
0
October 13, 2025
Common mistakes with SQL JOINs
- JOIN explosion from many-to-many relationships
- Filtering in WHERE instead of ON for LEFT JOINs
- Incorrect NULL handling on optional joins
- COUNT(*) vs COUNT(column) confusion
- Duplicate rows after joins
How JOIN questions are evaluated in interviews
Correctness beats performance; the right result set matters most.
Explain your join keys, assumptions, and how NULLs are treated.
Reasoning and clarity matter more than memorized syntax.
Related SQL concepts
SQL JOIN Interview FAQs
What is the difference between INNER JOIN and LEFT JOIN in interviews?
INNER JOIN returns only matching rows from both tables, while LEFT JOIN keeps all rows from the left table and fills unmatched right rows with NULLs. Interviewers often test whether you choose the correct join for required vs optional relationships.
When should I use a subquery instead of a JOIN?
Use a subquery when you need to filter or aggregate before joining, or when a correlated condition is clearer. JOINs are better for combining row-level data, while subqueries can simplify multi-step logic.