DoorDash·Software Engineer·Technical Phone Screen·Senior

Senior

Jun 2026

Summary

DoorDash backend interview that looked simple on paper but turned into a real exercise in C++ verbosity. The core task was straightforward but the implementation surface area was way bigger than I expected.

Questions Asked (1)

You have three independent APIs that each return a partial view of the same entity. Design and implement a new endpoint that accepts an ID, calls all three APIs, and returns a single merged response. Handle partial failures gracefully.

API & IntegrationsSystem DesignTechnical Trade-offs

Author's notes

The logic itself isn't hard to reason through but writing it out in C++ is a different story.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints, then outline a design that uses parallel calls with timeouts and a merge strategy that handles partial failures. Discuss trade-offs between consistency, latency, and complexity, and propose a concrete implementation with error handling and fallback behavior.

Pro tip: Emphasize idempotency and observability: ensure the endpoint can be safely retried and include logging/metrics for partial failures to aid debugging and monitoring.

1. Clarify Requirements and Constraints

Ask about expected latency, consistency needs, and failure semantics (e.g., should the endpoint fail if any API fails, or return partial data?).

2. Design the Aggregation Strategy

Decide on parallel vs. sequential calls, timeouts, retries, and how to merge responses (e.g., field-level merging, conflict resolution).

3. Handle Partial Failures

Define behavior when one or more APIs fail: return partial data with error details, use fallbacks, or degrade gracefully with cached data.

4. Implement with Resilience Patterns

Use circuit breakers, bulkheads, and timeouts to prevent cascading failures; ensure idempotency and proper error propagation.

5. Discuss Trade-offs and Monitoring

Weigh consistency vs. availability, latency vs. completeness; add logging, metrics, and alerts for partial failures.

Key Points to Mention

Parallel API calls with timeouts to minimize latency
Partial failure handling: return 200 with partial data and error metadata, or 207 Multi-Status
Merge strategy: field-level merging, conflict resolution (e.g., last-write-wins, priority)
Resilience patterns: circuit breakers, retries with backoff, fallbacks
Idempotency and caching to improve performance and reliability
Observability: logging, metrics, tracing for debugging and monitoring

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