Amazon·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say

Apr 2026

Summary

SQL pivot question for a BI Engineer role at Amazon. Pretty focused technical screen, just the one problem but it had some depth to it if you weren't already comfortable with conditional aggregation.

Questions Asked (1)

You have a table with department, revenue, and month columns. Write a SQL query that transforms it so each department gets one row, with separate columns for each month's revenue (Jan_Revenue, Feb_Revenue, and so on through December).

Data ModelingProduct Analytics & Metrics

Author's notes

The PIVOT keyword slipped my mind mid-interview so I went with CASE statements inside SUM() which works fine but felt messier to write out loud.

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AI HintsAI Generated

Suggested Approach

This is a pivot operation: transform rows into columns by aggregating revenue per department per month. Use conditional aggregation with CASE expressions inside SUM, grouped by department, to create one column per month. Alternatively, use the PIVOT operator if the SQL dialect supports it (e.g., SQL Server, Oracle).

Pro tip: Mention that the query should handle missing months by returning NULL or 0, and that the column order should follow the calendar. Also, note that if the database supports PIVOT, it can be more concise, but conditional aggregation is more portable.

1. Identify the pivot operation

Recognize that the task requires rotating rows into columns, with department as the grouping key and month as the spreading column.

2. Choose the pivot method

Decide between conditional aggregation (using CASE and SUM) or the PIVOT operator, based on the SQL dialect and portability requirements.

3. Write the conditional aggregation

For each month, create an expression like SUM(CASE WHEN month = 'Jan' THEN revenue ELSE 0 END) AS Jan_Revenue, and group by department.

4. Handle edge cases and ordering

Consider how to handle missing months (NULL vs 0), and ensure the output columns are ordered from January to December.

5. Test and optimize

Verify the query returns one row per department with correct values, and consider indexing or performance implications for large datasets.

Key Points to Mention

Conditional aggregation with CASE and SUM is a portable way to pivot data.
The PIVOT operator can simplify the query but is not available in all databases (e.g., MySQL, PostgreSQL).
Grouping by department ensures one row per department.
Use COALESCE or IFNULL to replace NULLs with 0 if needed.
Column aliases should match the required format (e.g., Jan_Revenue, Feb_Revenue).
Performance: pivoting can be expensive on large tables; consider pre-aggregation or indexing.

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