Amazon·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

Jun 2026

Summary

Amazon BI Engineer interview with a SQL question focused on ranking customers by daily purchase volume. Pretty straightforward scenario but the window function angle is where they're really testing you.

Questions Asked (1)

Given a table of prime membership date ranges and a table of orders with daily quantities, write a SQL query that returns, for each calendar day, the customer(s) with the highest total quantity sold. Handle ties by returning all tied customers.

Data ModelingProduct Analytics & Metrics

Author's notes

The aggregation part is fine, group by day and customer and sum the quantities.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

First, join the orders table with the prime membership table to filter orders to only those placed during active prime membership periods. Then, aggregate total quantity per customer per day, and use a window function like RANK() or DENSE_RANK() to identify the highest quantity per day, returning all customers with that rank.

Pro tip: Clarify assumptions about date ranges (inclusive/exclusive) and time zones upfront, and mention that you'd validate the query with edge cases like ties and missing days to ensure correctness.

1. Understand the schema and requirements

Identify the relevant columns in the prime membership table (customer_id, start_date, end_date) and orders table (customer_id, order_date, quantity). Clarify that 'calendar day' refers to each distinct order_date and that prime membership must be active on that day.

2. Join orders with prime memberships

Use an INNER JOIN between orders and prime memberships on customer_id, ensuring the order_date falls within the membership period (inclusive of start and end dates, or as specified). This filters to only prime orders.

3. Aggregate daily quantities per customer

Group by order_date and customer_id, summing the quantity to get total quantity per customer per day. This yields a daily leaderboard of customers by quantity.

4. Rank customers per day and filter top rank

Use a window function like RANK() or DENSE_RANK() over (PARTITION BY order_date ORDER BY total_quantity DESC) to assign ranks. Then, select only rows where rank = 1 to get the highest quantity customers, including ties.

5. Format and validate the output

Ensure the final result includes order_date, customer_id, and total_quantity, ordered by date. Discuss potential edge cases such as days with no orders (may need to handle separately) and ties.

Key Points to Mention

Use of window functions (RANK/DENSE_RANK) to handle ties efficiently without self-joins.
Importance of date range inclusivity and time zone considerations in membership validity.
Aggregation before ranking to avoid incorrect ranking due to multiple orders per day.
Handling of days with no orders (e.g., using a calendar table or left join) if required.
Performance considerations: indexing on customer_id and order_date, and partitioning in window functions.
Clarifying whether 'prime membership' means active on the order date or any overlapping period.

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