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Capital One·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
May 2026

Summary

Capital One data engineer interview, one SQL round that was heavier than I expected. The question looked straightforward on the surface but the join-plus-window-function combo with tie-handling tripped me up a bit.

Questions Asked (1)

Q1

Given an accounts table and a transactions table, find the top 3 customers per segment by total transaction amount over the last 30 days. A customer can have multiple accounts. Use window functions to rank within each segment, and include all tied customers at rank 3.

Data ModelingAlgorithms & Data StructuresTechnical Trade-offs
Author's notes

I got the basic join and the GROUP BY done pretty fast, but then sat there for an awkward moment on the tie-handling part.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the schema and business rules, then outline a SQL solution that joins accounts and transactions, filters transactions to the last 30 days, aggregates total transaction amount per customer per segment, and uses a window function like DENSE_RANK() to rank customers within each segment. Finally, filter to the top 3 ranks, ensuring ties at rank 3 are included.

Pro tip: Mention that you would validate the query's performance and correctness with edge cases, such as customers with multiple accounts and ties, and discuss indexing strategies on transaction date and customer ID to optimize the query.

1. Clarify requirements and schema

Ask about the table structures, relationships, and definitions (e.g., what constitutes a segment, how to handle multiple accounts per customer, and whether 'last 30 days' is relative to current date or a specific date).

2. Design the query logic

Outline the steps: join accounts to transactions, filter transactions to the last 30 days, aggregate total transaction amount per customer per segment, and apply a window function to rank customers within each segment.

3. Choose the right window function

Select DENSE_RANK() to handle ties correctly, ensuring that all customers tied at rank 3 are included. Explain why ROW_NUMBER() or RANK() would not be appropriate.

4. Write and optimize the SQL

Construct the SQL query with CTEs for readability, and discuss potential performance optimizations such as indexing and partitioning.

5. Test and validate

Describe how you would test the query with sample data, including edge cases like ties, customers with no transactions, and multiple accounts, to ensure correctness.

Key Points to Mention

  • Use of DENSE_RANK() over RANK() or ROW_NUMBER() to include ties at rank 3.
  • Aggregation of transaction amounts per customer per segment, considering multiple accounts per customer.
  • Filtering transactions to the last 30 days using a date condition (e.g., transaction_date >= CURRENT_DATE - INTERVAL '30 days').
  • Partitioning by segment in the window function to rank within each segment.
  • Performance considerations: indexing on transaction date and customer ID, and avoiding unnecessary joins.
  • Handling edge cases: customers with multiple accounts, ties, and customers with no transactions in the period.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.