← Amazon Interview Insights

Amazon·Data Scientist·Technical Phone Screen·Intermediate

Intermediate
May 2026

Summary

Amazon data scientist interview with a SQL-heavy question around customer segmentation and ranking. Pretty standard stuff but the tie-breaking follow-up is where things get interesting.

Questions Asked (1)

Q1

Given a transactions table, filter customers based on campaign criteria and then select exactly the top 5 by total order count. How do you handle ties when more than 5 customers qualify for that top-5 cutoff?

Data ModelingProduct Analytics & Metrics
Author's notes

The filtering and aggregation part was fine, GROUP BY user_id, ORDER BY order_cnt DESC, LIMIT 5, done.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

First, clarify the tie-breaking rule with the interviewer, then propose a deterministic method such as adding a secondary sort key (e.g., customer_id or earliest order date) to ensure exactly 5 rows. Alternatively, discuss using window functions like RANK or DENSE_RANK and explain the trade-offs of each approach.

Pro tip: Always state your tie-breaking assumption explicitly and ask if the business prefers a specific rule (e.g., most recent order, highest revenue). This shows you understand that ambiguous requirements can lead to inconsistent results in production.

1. Clarify the tie-breaking requirement

Ask the interviewer whether ties should be broken arbitrarily, by a secondary metric, or if all tied customers should be included (which may exceed 5). This ensures alignment before writing any SQL.

2. Filter customers based on campaign criteria

Write a subquery or CTE that selects only customers who meet the campaign conditions (e.g., signed up in a date range, made a purchase, etc.).

3. Compute total order count per customer

Aggregate the transactions table to get the total order count for each qualifying customer, using GROUP BY customer_id and COUNT(DISTINCT order_id) or similar.

4. Apply ranking and select top 5

Use a window function (ROW_NUMBER, RANK, or DENSE_RANK) ordered by total order count descending, and optionally a tie-breaker. Then filter to rank <= 5.

5. Explain the chosen tie-breaking method

Describe why you chose a particular ranking function and tie-breaker, and discuss the implications (e.g., ROW_NUMBER gives exactly 5, RANK may give more if ties).

Key Points to Mention

  • Use of window functions (ROW_NUMBER, RANK, DENSE_RANK) and their differences in handling ties.
  • Importance of a deterministic tie-breaker (e.g., customer_id, earliest order date, highest revenue) to ensure reproducibility.
  • Trade-offs between returning exactly 5 customers vs. including all tied customers (which may exceed 5).
  • Performance considerations: filtering before aggregation, indexing on join/group columns.
  • Business context: why the top 5 cutoff exists and how ties might affect campaign decisions.
  • Edge cases: customers with zero orders, duplicate orders, or null values in tie-breaker columns.

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