Upstart
Medium
Data ScientistManipulate data in R with dplyr joins and 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.
178Questions
49Companies
Easy 4 • Medium 4 • Hard 0Difficulty mix
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
Intuit
Medium
Data ScientistCompute churn and revenue churn in SQL
Data Manipulation (SQL/Python)
0
0
October 13, 2025
Pinterest
Medium
Data ScientistWrite windowed retention and ARPU SQL
Data Manipulation (SQL/Python)
0
0
October 13, 2025
Expedia
Medium
Data ScientistAudit and onboard unfamiliar datasets safely
Data Manipulation (SQL/Python)
0
0
October 13, 2025
Uber
Medium
Data ScientistClean, split, merge, and aggregate with pandas
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
Upstart
Medium
Data ScientistSolve SQL CTR and Python analytics tasks
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 ScientistAggregate exam scores with NULL handling
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 ScientistAnalyze Bookstore Data to Identify Top Payment Methods
Data Manipulation (SQL/Python)
0
0
August 4, 2025
Meta
Medium
Data ScientistRetrieve Ad Metrics and Rates for Last 7 Days
Data Manipulation (SQL/Python)
0
0
August 4, 2025
TikTok
Medium
Data ScientistCalculate Monthly Conversion Rate and Average Order Value
Data Manipulation (SQL/Python)
0
0
August 4, 2025
Amazon
Medium
Data ScientistIdentify Key Metrics for Monitoring Shipment Defects
Data Manipulation (SQL/Python)
0
0
August 4, 2025
Amazon
Medium
Data ScientistEnsure Correct Numeric Ordering in Visit ID Comparison
Data Manipulation (SQL/Python)
0
0
August 4, 2025
CloudTrucks
Medium
Data ScientistCalculate Average Rate and Cumulative Jobs by State
Data Manipulation (SQL/Python)
0
0
August 4, 2025
TikTok
Medium
Data ScientistIdentify Repeat Advertisers from Consecutive Weeks
Data Manipulation (SQL/Python)
0
0
August 4, 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.