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Google·Software Engineer·Onsite - System Design / Architecture·Senior

SeniorPrefer not to say
Apr 2026

Summary

System design round at Google for a software engineering role. One meaty question that took the full session, and I walked out unsure whether I'd covered enough of the right things.

Questions Asked (1)

Q1

Design a menu update and distribution system for a global restaurant chain, where menus are centrally managed but need to reach thousands of devices across many countries, support localization, handle offline scenarios, and correctly switch between breakfast/lunch/dinner windows.

System DesignData ModelingTechnical Trade-offs
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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and scale, then design a hierarchical data model with versioned menus and a CDN-based distribution system. Address offline support via local caching and time-based rules, and discuss trade-offs between consistency and availability.

Pro tip: Emphasize that menu updates should be atomic and versioned to avoid partial updates, and consider using a pub/sub system for real-time propagation to devices.

1. Clarify Requirements and Scale

Ask about number of devices, update frequency, localization needs, and offline duration. Establish consistency vs. availability trade-offs.

2. Design Data Model and Central Management

Define a versioned menu schema with localization support and time-based rules. Use a central service with a database and version control.

3. Design Distribution and Caching

Use a CDN to distribute menu bundles to edge locations. Devices pull updates periodically or via push notifications, with local caching for offline use.

4. Handle Offline and Time-Based Switching

Devices store menus locally and switch based on local time and date. Implement fallback to last known good menu if offline.

5. Address Consistency and Monitoring

Ensure atomic updates via versioning and checksums. Monitor device health and update success rates, with rollback capabilities.

Key Points to Mention

  • Versioned menu data model with localization (e.g., JSON with locale-specific fields)
  • CDN and edge caching for scalable distribution
  • Offline support via local storage and time-based rules
  • Atomic updates and rollback mechanisms
  • Trade-offs between consistency and availability (CAP theorem)
  • Monitoring and analytics for device status and update success

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