Join orders and transactions to find rolling 7-day average

Last updated: February 17, 2026

Quick Overview

Write a query joining orders and products to produce the combined rolling 7-day average.

Plaid
Data Manipulation (SQL/Python)
Data Scientist
Plaid
February 17, 2026
Data Scientist
Onsite
Data Manipulation (SQL/Python)
Medium

4

6

2,090 solved


Write a query joining orders and products to produce the combined rolling 7-day average.

This question from Plaid's Onsite tests practical data skills. The interviewer wants to see clean, efficient queries that handle edge cases like NULLs, duplicates, and large datasets.

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
Data cleaning and transformation
Common Table Expressions (CTEs)
NULL handling and COALESCE
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?
  • What indexes would you create to support this query?
  • How would you handle this if the data was spread across multiple databases?
  • Can you rewrite this without using subqueries?
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