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

SeniorPrefer not to say
Jun 2026

Summary

Google SWE design round where I had to build out a full wait-list system from scratch. Pretty open-ended, which sounds fun until you're actually in the hot seat trying to justify every data structure choice in real time.

Questions Asked (1)

Q1

Design and implement a complete wait-list system supporting joining and leaving the queue, viewing the full queue in order, and efficiently retrieving the top K or bottom K entries. Walk through your class design, backing data structures, time complexities, and how you'd extend it for priorities, persistence, and concurrency.

System DesignAlgorithms & Data StructuresTechnical Trade-offs
Author's notes

I started with a doubly linked list plus a hash map for O(1) join, leave, and position lookup, which felt solid.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints, then propose a class design with a doubly linked list and hash map for O(1) join/leave and O(n) ordered traversal. For top/bottom K, discuss augmenting with a balanced BST or heap, and address extensions for priorities, persistence, and concurrency with trade-offs.

Pro tip: Demonstrate awareness of real-world constraints by discussing how to handle concurrency with fine-grained locking or lock-free structures, and mention persistence options like write-ahead logging or snapshots.

1. Clarify Requirements

Ask about expected queue size, frequency of operations, priority semantics, persistence needs, and concurrency requirements to tailor the design.

2. Core Data Structure Design

Propose a doubly linked list for O(1) insertion/removal and a hash map for O(1) access by ID, enabling ordered traversal in O(n).

3. Efficient Top/Bottom K Retrieval

Augment with a balanced BST (e.g., order-statistic tree) or a heap for O(log n) insert/delete and O(k) retrieval, discussing trade-offs.

4. Extensions: Priorities, Persistence, Concurrency

For priorities, use a priority queue or multiple queues; for persistence, discuss logging or snapshots; for concurrency, propose locking strategies or lock-free approaches.

5. Complexity Analysis and Trade-offs

Summarize time and space complexities for each operation and justify design choices, acknowledging limitations and alternatives.

Key Points to Mention

  • Doubly linked list + hash map for O(1) join/leave and O(n) ordered view
  • Balanced BST or heap for O(log n) top/bottom K retrieval
  • Priority handling via multiple queues or priority queue with stable ordering
  • Persistence through write-ahead logging or periodic snapshots
  • Concurrency control with fine-grained locks or lock-free data structures
  • Trade-offs between simplicity, performance, and scalability

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