Zoox·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

Jul 2026

Summary

SQL-heavy technical screen for a data engineer role at Zoox. Two questions, both involving the same transactions dataset, with the second one being a window function problem that I felt okay about but probably could've been cleaner.

Questions Asked (2)

Given a transactions table and a vendors table, write a SQL query to find the top 3 vendors by total purchase dollars in the last 2 years. Return vendor_id and total_dollars_charged, sorted highest to lowest.

Data ModelingProduct Analytics & Metrics

Author's notes

Pretty standard aggregation question.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the schema and assumptions (e.g., date column, transaction amount, vendor_id in transactions). Then write a query that filters transactions to the last 2 years, aggregates total dollars per vendor, joins with the vendors table if needed, and finally selects the top 3 vendors by total dollars in descending order.

Pro tip: Mention that you would use a date function like DATEADD or INTERVAL to dynamically calculate the last 2 years relative to the current date, rather than hardcoding dates. Also, consider indexing on the date column for performance if the table is large.

1. Clarify schema and assumptions

Ask about the column names and data types, especially the date column and amount column in the transactions table, and how vendors are identified. Confirm that 'last 2 years' means from the current date minus 2 years to today.

2. Filter transactions for the last 2 years

Use a WHERE clause with a date function (e.g., DATEADD(year, -2, CURRENT_DATE) or INTERVAL '2 years') to select only transactions within the last 2 years.

3. Aggregate total dollars per vendor

Group by vendor_id and sum the transaction amount to get total_dollars_charged for each vendor.

4. Join with vendors table if necessary

If vendor details are needed or to ensure only valid vendors are included, join the aggregated results with the vendors table on vendor_id.

5. Select top 3 and sort

Order the results by total_dollars_charged descending and limit to 3 rows. Return vendor_id and total_dollars_charged.

Key Points to Mention

Use of date functions to dynamically calculate the last 2 years (e.g., DATEADD, INTERVAL, or equivalent).
Aggregation with SUM and GROUP BY on vendor_id.
Handling of NULLs or missing data (e.g., COALESCE for amounts).
Ordering with ORDER BY total_dollars_charged DESC and LIMIT 3 (or TOP 3 depending on SQL dialect).
Consideration of performance: indexing on transaction date and vendor_id.
Assumption that transactions table has vendor_id and amount columns; if not, join with vendors table to get vendor_id.

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

Using the same dataset, for each (state_province, country) pair, find the top 3 vendors by total purchase dollars in the last 2 years. Return state_province, country, vendor_id, total_dollars, and vendor_rank. Use dense ranking so ties get the same rank.

Data ModelingAlgorithms & Data Structures

Author's notes

This is where it got interesting.

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AI HintsAI Generated

Suggested Approach

Use a window function with DENSE_RANK() partitioned by state_province and country, ordered by total purchase dollars descending. First filter the dataset to the last 2 years, then aggregate total dollars per vendor per location, and finally apply the ranking and filter to top 3.

Pro tip: Clarify the definition of 'last 2 years' (e.g., relative to current date or max date in dataset) and confirm whether ties should be broken arbitrarily or if all tied vendors should be included. Also, consider performance implications of window functions on large datasets and mention indexing or partitioning strategies.

1. Filter by date range

Restrict the dataset to records from the last 2 years. Determine the reference date (e.g., current date or maximum date in the data) and apply the filter accordingly.

2. Aggregate total purchase dollars

Group by state_province, country, and vendor_id, then sum the purchase dollars to get total_dollars per vendor per location.

3. Apply dense ranking

Use the DENSE_RANK() window function, partitioned by state_province and country, ordered by total_dollars descending, to assign vendor_rank.

4. Filter top 3 vendors

Select only rows where vendor_rank <= 3, ensuring ties are handled correctly (dense rank may return more than 3 vendors if ties occur).

5. Format output

Return the required columns: state_province, country, vendor_id, total_dollars, and vendor_rank. Order the results for readability, e.g., by state_province, country, and vendor_rank.

Key Points to Mention

Use of DENSE_RANK() to handle ties correctly, as opposed to ROW_NUMBER() or RANK().
Partitioning by state_province and country to rank vendors within each location.
Date filtering logic: define 'last 2 years' clearly, possibly using a subquery to get the max date or using CURRENT_DATE.
Aggregation before ranking: sum purchase dollars per vendor per location.
Performance considerations: indexing on date and location columns, and potential use of CTEs for readability.
Handling of ties: dense rank may return more than 3 vendors; confirm if that's acceptable or if additional tie-breaking is needed.

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