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Amazon·Data Scientist·Technical Phone Screen·Intermediate

Intermediate
Apr 2026

Summary

SQL-heavy technical screen for a Data Scientist role at Amazon. Three questions, all focused on querying event and session tables, nothing behavioral at all. Pretty straightforward if you're comfortable with GROUP BY and window functions, but the last one tripped me up a bit.

Questions Asked (3)

Q1

Given a table of user events, write a SQL query to count the total number of events per user.

Product Analytics & Metrics
Author's notes

Easiest of the three.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the table schema and the definition of an event, then write a simple GROUP BY query to count events per user. Mention handling of NULLs, duplicates, and performance considerations for large datasets.

Pro tip: At Amazon, interviewers value candidates who proactively discuss data scale and query optimization. Mention how you would handle billions of events, such as using partitioning or approximate counting if exact counts are not required.

1. Clarify Requirements

Ask about the table schema, what constitutes an event, and whether the count should be distinct or total. Confirm if there are any filters or time windows.

2. Write Basic Query

Use SELECT user_id, COUNT(*) AS event_count FROM events GROUP BY user_id. Ensure you handle any NULL user_ids appropriately.

3. Consider Edge Cases

Discuss handling of duplicate events, NULL values, and whether to include users with zero events. Mention if a LEFT JOIN with a users table is needed.

4. Optimize for Scale

Mention indexing on user_id, partitioning, or using approximate algorithms like HyperLogLog if exact counts are not required. Discuss trade-offs.

5. Validate and Explain

Walk through the query logic, explain the output, and suggest ways to validate results, such as checking a few users manually.

Key Points to Mention

  • Use of GROUP BY and COUNT(*) for aggregation
  • Handling NULL user_ids (e.g., filtering or grouping them separately)
  • Distinguishing between COUNT(*) and COUNT(DISTINCT event_id) if duplicates exist
  • Performance considerations for large-scale data (indexes, partitioning)
  • Potential need to join with a users table to include users with zero events
  • Clarity on whether the count should be per user per day or overall

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

Q2

Using the same events table, return each user's earliest and latest event timestamps.

Product Analytics & MetricsData Modeling
Author's notes

Also pretty basic.

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AI HintsAI Generated

Suggested Approach

Use a GROUP BY on the user identifier and apply MIN and MAX to the event timestamp column to get each user's first and last event times. Clarify the timestamp column name and whether the table includes any filters or time zones that could affect the result.

Pro tip: Mention that this is a classic 'first and last activity' query and that in production you'd often pair it with a window function or a self-join to also retrieve the full event details for those timestamps, not just the times.

1. Clarify the schema and requirements

Confirm the exact column names for the user identifier and event timestamp, and check whether the table has any partitioning or time zone considerations. Ask if the result should include only users with at least one event or all users.

2. Write the core aggregation query

Use SELECT user_id, MIN(event_timestamp) AS earliest_event, MAX(event_timestamp) AS latest_event FROM events GROUP BY user_id. This directly answers the question with minimal complexity.

3. Consider edge cases and performance

Discuss how NULL timestamps or duplicate events would be handled, and mention that grouping by user_id is efficient if the table is indexed or partitioned on user_id. If the table is huge, suggest filtering by a date range if the business question allows it.

4. Extend to a more realistic scenario (optional)

If the interviewer wants more, show how to retrieve the full event rows for those timestamps using a window function like ROW_NUMBER() or a self-join, which is common in product analytics to get first/last event details.

Key Points to Mention

  • Use of GROUP BY with MIN and MAX aggregate functions
  • Handling of NULLs and ensuring the timestamp column is of a comparable type
  • Performance considerations: indexing, partitioning, and filtering by date range
  • Difference between getting just the timestamps vs. the full event records
  • Time zone normalization if events come from multiple regions
  • Potential need to deduplicate events if the table has duplicates

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

Q3

Join the events and sessions tables to find the user whose single session has the longest duration, and return both the user ID and that duration.

Data ModelingAlgorithms & Data Structures
Author's notes

This is where I fumbled a little.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the table schemas and the definition of 'single session' (e.g., a session with no other sessions for that user). Then write a SQL query that joins events and sessions, computes the duration per session, filters to users with exactly one session, and selects the user with the maximum duration. Alternatively, use a window function to rank sessions by duration and filter for the top one, ensuring you handle ties appropriately.

Pro tip: Always clarify ambiguous terms like 'single session' and 'duration' (e.g., is it session length or event duration?) before writing code. Also, consider edge cases such as ties in duration and users with multiple sessions, and discuss how you would handle them.

1. Clarify requirements and schema

Ask clarifying questions about the table structures, what 'single session' means (e.g., user has exactly one session), and how duration is calculated (e.g., session end time minus start time).

2. Identify relevant columns and join keys

Determine the join condition between events and sessions (likely session_id) and the columns needed: user_id, session start/end times or event timestamps to compute duration.

3. Compute session durations

Calculate the duration for each session, either from session start/end times or by aggregating event timestamps (e.g., max event time minus min event time per session).

4. Filter to users with exactly one session

Use a subquery or window function to count sessions per user and keep only those with a count of 1.

5. Select the user with the longest duration

Order the filtered results by duration descending and limit to 1, or use a window function like ROW_NUMBER() to pick the top session, handling ties as needed.

Key Points to Mention

  • Clarify ambiguous terms: 'single session' and 'duration'.
  • Use appropriate SQL joins (INNER JOIN) between events and sessions.
  • Compute duration using timestamps (e.g., DATEDIFF, TIMESTAMPDIFF, or subtraction).
  • Filter users with exactly one session using GROUP BY and HAVING COUNT(*) = 1.
  • Use ORDER BY duration DESC LIMIT 1 or window functions (ROW_NUMBER, RANK) to get the top result.
  • Discuss handling ties and edge cases (e.g., multiple users with same max duration).

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