Join messages and impressions to find percentile rank
Last updated: October 10, 2025
Quick Overview
Write a query joining messages and users to produce the combined percentile rank.
Stripe
Data Manipulation (SQL/Python)
Data Scientist
Stripe
October 10, 2025Data Scientist
Phone Screen
Data Manipulation (SQL/Python)
Hard
10
5
1,877 solved
Write a query joining messages and users to produce the combined percentile rank.
Stripe asks this during the Phone Screen because data engineering skills are critical for the role. You should be comfortable with complex joins, window functions, CTEs, and performance optimization.
What the Interviewer Expects
- Solve complex analytical problems with elegant, readable SQL
- Optimize queries for large-scale datasets with partitioning and indexing
- Use recursive CTEs, lateral joins, and advanced window functions
- Design the data model alongside the query solution
- Discuss trade-offs between SQL and programmatic approaches (Python/pandas)
- Consider the operational aspects: query scheduling, incremental processing
Key Topics to Cover
JOIN types and when to use each
Date/time manipulation
Aggregate functions and GROUP BY
Subqueries and correlated subqueries
How to Approach This
- Clarify the schema and expected output format before writing queries.
- Use CTEs (WITH clauses) to break complex queries into readable steps.
- Consider window functions (ROW_NUMBER, RANK, LAG, LEAD) for ranking and sequential analysis.
- Watch for NULLs, duplicates, and edge cases in JOINs and GROUP BY.
- For pandas, prefer vectorized operations over row-by-row iteration.
Possible Follow-up Questions
- How would you handle slowly changing dimensions in this scenario?
- Can you rewrite this without using subqueries?
- How would you validate the correctness of your query results?
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Practice SQL ProblemsSample Answer
Problem Understanding
In this problem, we have two main datasets: a messages table and a users table. The messages table contains information about messages sent by users, including attributes like message ID, user I...
Approach
- Identify the necessary columns: Determine which columns from
messagesandusersare needed for the analysis, primarily focusing on user ID for joining and message ID for ranking. - **Join ...
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