Salesforce·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

Jun 2026

Summary

SQL-heavy technical screen for a full-stack role at Salesforce. One question, but it had enough moving parts to trip you up if you're not careful about date filtering across different database engines.

Questions Asked (1)

Given a transactions table with user_id, amount, and transaction_date columns, write a SQL query to find the user with the highest total spend in the previous calendar month. How do you handle the date filtering across different DB engines, and what happens if two users are tied?

Data ModelingTechnical Trade-offs

Author's notes

The core aggregation is straightforward but I fumbled the date part a bit.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the schema and the definition of 'previous calendar month' relative to the current date, then write a portable SQL query that filters transactions to that month, aggregates total spend per user, and selects the top spender. Address date filtering across DB engines by using functions like DATE_TRUNC or EXTRACT, and handle ties by either returning all tied users or using a deterministic tiebreaker.

Pro tip: Mention that you would confirm the expected behavior for ties with the interviewer, and if the business wants a single user, use a deterministic tiebreaker like the earliest transaction date or lowest user_id. Also, note that using functions like DATE_TRUNC can prevent index usage, so consider precomputing date ranges for performance.

1. Clarify requirements and schema

Confirm the table structure, the definition of 'previous calendar month' (e.g., relative to CURRENT_DATE), and how ties should be resolved. Ask if the result should include all tied users or just one.

2. Filter transactions for the previous month

Use database-specific date functions to filter transactions where transaction_date falls within the previous calendar month. For portability, consider using EXTRACT or DATE_TRUNC, or compute start and end dates in the application.

3. Aggregate total spend per user

Group by user_id and sum the amount to get total spend for each user in that month. Ensure you handle NULLs and data types appropriately.

4. Identify the top spender(s)

Order the aggregated results by total spend descending and limit to 1, or use a window function like RANK() to handle ties. If ties should be returned, use RANK() and filter for rank = 1.

5. Address cross-engine compatibility and performance

Explain how the query would differ across engines (e.g., PostgreSQL, MySQL, SQL Server) and suggest using date range conditions for better index usage. Mention that if ties are possible, the query should be adjusted accordingly.

Key Points to Mention

Definition of 'previous calendar month' and how to compute it using date functions like DATE_TRUNC, EXTRACT, or DATEADD.
Cross-database compatibility: differences in date functions (e.g., PostgreSQL's DATE_TRUNC vs. MySQL's DATE_FORMAT vs. SQL Server's DATEFROMPARTS).
Tie handling: using RANK() or DENSE_RANK() to return all top spenders, or a deterministic tiebreaker (e.g., lowest user_id) if only one is needed.
Performance considerations: avoiding functions on the date column to allow index usage, or using a computed date range.
Edge cases: users with no transactions in the month, negative amounts (refunds), and timezone considerations.
Clarifying questions: confirm if 'previous calendar month' means the full month before the current date, and whether to include users with zero spend.

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