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DoorDash·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say
Apr 2026Remote

Summary

DoorDash coding screen focused on a dasher payment calculation problem. The constraint about no auxiliary data structures was the real twist, and the edge case conversation got uncomfortable fast.

Questions Asked (1)

Q1

Design and implement an API that ingests a stream of delivery driver events (shift start, pickup, dropoff, shift end with timestamps) and computes the driver's total payment for a shift using a rule like base pay per delivery plus per-mile plus per-minute, with minimum guarantees. You must process events in a single pass using only a small number of running counters, no arrays, sets, or hashmaps.

API & IntegrationsAlgorithms & Data StructuresTechnical Trade-offs
Author's notes

The single-pass constraint is where I tripped up initially.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the event schema, payment rules, and constraints (single pass, O(1) space). Then outline a state machine that tracks shift state and accumulates running totals (deliveries, miles, minutes) using only scalar variables, and finally compute the final payment with minimum guarantees applied at shift end.

Pro tip: Explicitly call out edge cases like missing shift end, out-of-order events, and zero deliveries, and explain how your design handles them without extra memory—this shows production readiness.

1. Clarify requirements and constraints

Ask about event types, timestamp format, payment formula details, minimum guarantees, and whether events are guaranteed ordered. Confirm the single-pass and O(1) space constraints.

2. Define state and counters

Identify the minimal state needed: shift active flag, last event timestamp, and running totals for deliveries, miles, and minutes. Use only scalar variables.

3. Design the event processing logic

For each event, update state and counters accordingly: on shift start, initialize; on pickup/dropoff, increment deliveries and accumulate distance/time; on shift end, finalize.

4. Compute payment with guarantees

At shift end, calculate base pay + per-mile + per-minute, then apply minimum guarantees (e.g., per delivery, per hour) by taking the max of computed and guaranteed amounts.

5. Discuss trade-offs and edge cases

Explain how the design handles out-of-order events, missing shift end, and zero deliveries. Mention that this approach is scalable and memory-efficient.

Key Points to Mention

  • Event schema and state machine (shift start, pickup, dropoff, shift end)
  • Running counters for deliveries, miles, and minutes using only scalars
  • Payment formula: base pay per delivery + per-mile + per-minute
  • Minimum guarantees: per delivery, per hour, or per shift, applied at finalization
  • Handling out-of-order events or missing shift end without extra memory
  • Time and space complexity: O(n) time, O(1) space

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