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Jane Street·Software Engineer·Onsite - System Design / Architecture·Senior

SeniorPrefer not to say
May 2026

Summary

Jane Street system design round, one big question about designing a file system service from scratch. They wanted the full stack: API design, storage layout, consistency, and how you'd scale it. Pretty intense for a single question.

Questions Asked (1)

Q1

Design a file system service covering the functional API, data model, storage layout, consistency and concurrency, and scaling strategy. Discuss trade-offs in metadata service design.

System DesignTechnical Trade-offsData Modeling
Author's notes

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Suggested Approach

Start by clarifying requirements and scope, then systematically design the API, data model, storage layout, consistency/concurrency, and scaling. Throughout, explicitly discuss trade-offs, especially in metadata service design, and relate them to Jane Street's performance-critical, low-latency environment.

Pro tip: Emphasize how your design choices impact latency and throughput, and be prepared to dive deep into one or two trade-offs (e.g., centralized vs distributed metadata) with concrete examples. Show awareness of Jane Street's culture by prioritizing simplicity, correctness, and performance.

1. Clarify Requirements and Scope

Ask questions to understand expected scale, consistency needs, latency requirements, and use cases (e.g., small files, large files, random vs sequential access). Define functional and non-functional requirements.

2. Design Functional API and Data Model

Define core operations (create, read, write, delete, list, etc.) and the data model (files, directories, metadata, permissions). Consider hierarchical namespace and how to represent it.

3. Design Storage Layout and Metadata Service

Decide on block storage, replication, and placement. For metadata, compare centralized vs distributed designs (e.g., single metadata server vs sharded, replicated). Discuss trade-offs in consistency, latency, and scalability.

4. Address Consistency and Concurrency

Choose consistency model (strong vs eventual) and explain how it affects operations. Describe concurrency control (locking, versioning, leases) for metadata and data operations.

5. Outline Scaling Strategy and Trade-offs

Explain how to scale metadata and data layers (sharding, replication, caching). Summarize key trade-offs, especially in metadata service design, and how they align with requirements.

Key Points to Mention

  • Metadata service design trade-offs: centralized (simple, consistent, but bottleneck) vs distributed (scalable, but complex consistency).
  • Consistency models: strong vs eventual, and their impact on operations like directory listing and file updates.
  • Concurrency control: locking, leases, optimistic concurrency, and how to handle conflicts.
  • Storage layout: block size, replication factor, placement policies, and tiering (hot vs cold).
  • Scaling strategies: sharding metadata by namespace, caching metadata, and using distributed consensus (e.g., Paxos/Raft) for metadata replication.
  • Latency and throughput considerations: how design choices affect performance, especially for small file operations.

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