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DoorDash·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say
Jun 2026Remote

Summary

DoorDash software engineering interview with a meaty coding problem centered on dasher pay period calculations. One question but it had a lot of layers to it.

Questions Asked (1)

Q1

Given a dasher ID, a local pay-period interval, and a list of order events (each with an order ID, dasher ID, event type of either ACCEPT or FULFILL, and a LocalDateTime timestamp), write a function that returns the active duration for each completed order in the interval and the total active duration across all completed orders. Events may arrive unsorted. After coding it up, explain the time and space complexity, and describe how you'd extend the solution to calculate payment when pay rules depend on active duration.

Algorithms & Data StructuresTechnical Trade-offsSystem Design
Author's notes

The core pairing logic wasn't too bad once I decided to group events by orderId and sort within each group.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and edge cases (e.g., overlapping intervals, missing events, timezone handling). Then design a solution that groups events by order ID, sorts them by timestamp, and computes active duration for completed orders within the pay period. Finally, analyze complexity and discuss extensibility for payment rules.

Pro tip: Mention that you would use a hash map to group events by order ID and sort each group's events by timestamp, which handles unsorted input efficiently. Also, proactively discuss how to handle incomplete orders (e.g., ACCEPT without FULFILL) and whether to include them in the total.

1. Clarify Requirements and Edge Cases

Ask about the definition of 'active duration' (e.g., time between ACCEPT and FULFILL), how to handle orders with missing events, and whether the interval is inclusive. Confirm if only completed orders (with both ACCEPT and FULFILL) should be considered.

2. Design the Algorithm

Group events by order ID using a hash map. For each order, sort events by timestamp, then find the ACCEPT and FULFILL events. Compute the duration if both exist and the FULFILL timestamp falls within the pay period. Sum durations for all completed orders.

3. Implement and Test

Write clean code with helper functions for grouping and duration calculation. Test with unsorted events, orders spanning the interval boundary, and orders with missing events.

4. Analyze Complexity

Explain that grouping takes O(n) time, sorting each group takes O(k log k) where k is events per order, leading to O(n log n) worst-case time. Space is O(n) for storing grouped events.

5. Discuss Extensibility for Payment

Describe how to extend the solution to calculate payment by applying pay rules (e.g., base rate + per-minute rate) to each order's active duration. Mention the need for a rules engine or strategy pattern to handle varying pay rules.

Key Points to Mention

  • Handling unsorted events by grouping and sorting per order
  • Definition of active duration as time between ACCEPT and FULFILL
  • Filtering orders to only those completed within the pay period
  • Time complexity: O(n log n) due to sorting, space complexity: O(n)
  • Edge cases: missing events, overlapping intervals, timezone considerations
  • Extensibility: using strategy pattern for pay rules based on active duration

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