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

SeniorPrefer not to say
Apr 2026

Summary

Google system design round, one question about building a hotel booking service. Not a lot of context given upfront so I spent probably too long clarifying scope before actually designing anything.

Questions Asked (1)

Q1

Design a hotel booking service.

System DesignData ModelingTechnical Trade-offs
Author's notes

I started with the data model and search before thinking about the reservation flow, which was probably backwards.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and scale, then design a high-level architecture covering core components like search, booking, and payment. Dive into data modeling and trade-offs, focusing on consistency, availability, and scalability.

Pro tip: Emphasize idempotency and distributed transactions to handle double bookings and payment failures, showing you understand real-world reliability challenges.

1. Clarify Requirements

Ask about functional and non-functional requirements: user scenarios, scale (e.g., daily bookings, peak load), consistency needs, and latency targets.

2. High-Level Design

Sketch main components: API gateway, search service, booking service, payment service, inventory management, and databases. Define interactions.

3. Data Modeling

Design schemas for hotels, rooms, availability, bookings, and users. Discuss indexing, sharding, and caching strategies for performance.

4. Deep Dive into Critical Flows

Detail search (e.g., geospatial queries, filters) and booking (e.g., locking, transactions, idempotency) flows, addressing concurrency and consistency.

5. Trade-offs and Scalability

Discuss trade-offs (e.g., SQL vs NoSQL, strong vs eventual consistency) and scaling strategies (e.g., caching, read replicas, partitioning).

Key Points to Mention

  • Handling double bookings with distributed locks or optimistic concurrency control
  • Idempotent booking and payment APIs to ensure exactly-once processing
  • Caching strategies for search results and availability to reduce latency
  • Database sharding and replication for scalability and fault tolerance
  • Event-driven architecture for asynchronous processing (e.g., notifications, inventory updates)
  • Monitoring and alerting for system health and booking anomalies

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