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Reinforce Labs·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Jul 2026

Summary

SQL question for a Software Engineer role at Reinforce Labs, focused on inventory tracking with conditional aggregation and outer joins. Pretty straightforward premise but a few edge cases that could trip you up if you're not careful.

Questions Asked (1)

Q1

Given a products table and a stock_movements table (with movement types INCOMING, OUTGOING, and RETURN), write a SQL query that returns each product's current stock level, calculated as total incoming plus returns minus outgoing. Products with zero stock should still appear in the results, ordered by product_id.

Data ModelingTechnical Trade-offs
Author's notes

My first instinct was a simple GROUP BY with SUM, but I almost forgot about the RETURN type adding back to stock, which would've tanked the numbers.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the schema and edge cases, then outline a query using a LEFT JOIN from products to an aggregated stock_movements subquery, using conditional SUM to compute net stock. Emphasize that the LEFT JOIN ensures products with zero stock appear, and discuss ordering and potential performance considerations.

Pro tip: Mention that you'd verify whether stock_movements can have NULL product_id or movement types outside the three given, and consider using a CTE for readability and easier debugging.

1. Clarify requirements and schema

Confirm the columns, data types, and whether all movement types are covered. Ask about expected data volume and any constraints.

2. Design the aggregation

Use conditional aggregation (SUM with CASE) on stock_movements to compute net stock per product, grouping by product_id.

3. Ensure all products are included

Use a LEFT JOIN from products to the aggregated subquery, and handle NULLs with COALESCE to default to 0.

4. Order and finalize

Order by product_id ascending, and consider if any additional filters or formatting are needed.

5. Discuss trade-offs and optimizations

Talk about indexing, alternative approaches (e.g., using a CTE or window functions), and performance implications for large datasets.

Key Points to Mention

  • Use of LEFT JOIN to include products with no movements
  • Conditional aggregation with CASE to handle INCOMING, OUTGOING, and RETURN
  • COALESCE or IFNULL to convert NULL sums to 0
  • Grouping by product_id in the subquery
  • Ordering by product_id as specified
  • Potential performance considerations and indexing on product_id and movement_type

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