Calculate average revenue per date

Last updated: July 25, 2025

Quick Overview

Write a query to compute average revenue grouped by user, handling edge cases like nulls and duplicates.

Plaid
Data Manipulation (SQL/Python)
Data Scientist
Plaid
July 25, 2025
Data Scientist
Technical Screen
Data Manipulation (SQL/Python)
Medium

10

8

2,475 solved


Write a query to compute average revenue grouped by user, handling edge cases like nulls and duplicates.

Plaid asks this during the Technical 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
  • Use advanced SQL features: window functions, CTEs, subqueries
  • Write efficient queries that avoid common performance pitfalls
  • Handle complex data transformations with multiple joins and aggregations
  • Discuss indexing strategy and query optimization
  • Address data quality issues: duplicates, missing values, outliers
Key Topics to Cover
Date/time manipulation
JOIN types and when to use each
Window functions (ROW_NUMBER, RANK, LAG, LEAD)
Index optimization and query performance
How to Approach This
  1. Clarify the schema and expected output format before writing queries.
  2. Use CTEs (WITH clauses) to break complex queries into readable steps.
  3. Consider window functions (ROW_NUMBER, RANK, LAG, LEAD) for ranking and sequential analysis.
  4. Watch for NULLs, duplicates, and edge cases in JOINs and GROUP BY.
  5. For pandas, prefer vectorized operations over row-by-row iteration.
Possible Follow-up Questions
  • How would you optimize this query for a table with 100 million rows?
  • How would you handle slowly changing dimensions in this scenario?
  • What would you do if this query needs to run every 5 minutes?
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Solution Pattern

```sql WITH filtered_data AS ( SELECT * FROM main_table WHERE condition = 'value' AND date_col >= '2024-01-01' ), aggregated AS ( SELECT ...


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