Join rides and sessions to find engagement score
Last updated: August 8, 2025
Quick Overview
Write a query joining rides and transactions to produce the combined engagement score.
Plaid
Data Manipulation (SQL/Python)
Data Scientist
Plaid
August 8, 2025Data Scientist
Technical Screen
Data Manipulation (SQL/Python)
Medium
81
10
2,647 solved
Write a query joining rides and transactions to produce the combined engagement score.
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
Window functions (ROW_NUMBER, RANK, LAG, LEAD)
Subqueries and correlated subqueries
JOIN types and when to use each
Data cleaning and transformation
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?
- How would you handle this if the data was spread across multiple databases?
- What indexes would you create to support this query?
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Practice SQL ProblemsSample Answer
Problem Understanding
In this task, we need to join two datasets: rides and transactions. The rides dataset contains information about user rides, including user IDs and timestamps, while the transactions dataset i...
Approach
- Identify Key Columns: Determine the common keys for joining the tables, which will likely be user IDs.
- Join the Datasets: Use an INNER JOIN to combine the rides and transactions based o...
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