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Walmart Labs·Software Engineer·Onsite - System Design / Architecture·Senior

Senior
Jun 2026

Summary

System design round at Walmart Labs for a software engineer role. The whole session was basically one big question about building a multi-carrier shipping platform, and they went pretty deep on almost every layer of it.

Questions Asked (1)

Q1

Design a customer-facing package delivery service that integrates with multiple shipping carriers like UPS, USPS, and FedEx. Walk through the full system: customer API, carrier abstraction, rate shopping, label generation, async tracking, failure handling, idempotency, scaling, and observability.

System DesignAPI & IntegrationsTechnical Trade-offs
Author's notes

This is a lot to cover in one session.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and scale, then design a layered architecture with a customer-facing API, a carrier abstraction layer, and asynchronous workers for tracking and label generation. Walk through the critical flows—rate shopping, label creation, and tracking—highlighting idempotency, failure handling, and observability at each step.

Pro tip: Emphasize idempotency keys and retry strategies with exponential backoff for carrier calls, and discuss how you'd handle carrier-specific quirks (e.g., different label formats, tracking statuses) via adapters. Also, mention that you'd use a circuit breaker per carrier to prevent cascading failures.

1. Clarify Requirements and Scale

Ask about expected volume (e.g., shipments per day), latency requirements, supported carriers, and whether the system is customer-facing (B2C) or also for internal ops. Define SLAs for rate shopping and tracking updates.

2. High-Level Architecture

Outline the main components: API gateway, customer service (REST/GraphQL), carrier abstraction layer, rate shopping service, label generation service, tracking service (async workers), and data stores (SQL for orders, NoSQL for tracking events, cache for rates).

3. Deep Dive into Critical Flows

Walk through rate shopping (parallel calls to carriers, caching, fallback), label generation (idempotent requests, carrier-specific formats, storage), and tracking (polling/webhooks, event processing, customer notifications).

4. Address Cross-Cutting Concerns

Discuss idempotency (keys for label creation, deduplication), failure handling (retries, dead-letter queues, circuit breakers), scaling (horizontal scaling of stateless services, partitioning by customer/order), and observability (metrics, logging, tracing, alerting).

5. Trade-offs and Extensions

Summarize key trade-offs (e.g., sync vs async tracking, caching vs real-time rates) and suggest future improvements like machine learning for carrier selection or support for international carriers.

Key Points to Mention

  • Carrier abstraction layer using adapter pattern to encapsulate carrier-specific APIs and data formats.
  • Idempotency keys for label generation and rate requests to prevent duplicate charges and shipments.
  • Asynchronous tracking via webhooks or polling with a message queue (e.g., Kafka, SQS) and event-driven updates.
  • Failure handling: retries with exponential backoff, circuit breakers per carrier, and dead-letter queues for poison messages.
  • Scalability: stateless services, horizontal scaling, database sharding/partitioning, and caching of rate quotes.
  • Observability: structured logging, distributed tracing (e.g., OpenTelemetry), metrics (latency, error rates), and alerting on carrier failures.

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