Calculate percentile rank per date

Last updated: July 3, 2025

Quick Overview

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

Coinbase
Data Manipulation (SQL/Python)
Data Scientist
Coinbase
July 3, 2025
Data Scientist
Phone Screen
Data Manipulation (SQL/Python)
Medium

219

3

1,970 solved


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

Data manipulation questions at Coinbase test your ability to work with real-world datasets. This Phone Screen question evaluates your SQL proficiency, understanding of data modeling, and ability to derive insights from raw data.

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
Subqueries and correlated subqueries
Date/time manipulation
Pandas vectorized operations and groupby
Aggregate functions and GROUP BY
JOIN types and when to use each
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
  • What would you do if this query needs to run every 5 minutes?
  • How would you handle slowly changing dimensions in this scenario?
  • How would you optimize this query for a table with 100 million rows?
  • How would you handle this if the data was spread across multiple databases?
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Sample Answer
Approach

Break the problem into logical steps before writing SQL. Think about: 1. What tables do I need to join and on which keys? 2. What filtering (WHERE) d...

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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