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Optiver·Software Engineer·Technical Phone Screen·Junior

Junior
Jul 2026

Summary

First round for the Optiver SWE intern role was pretty standard: intro, resume chat, then a coding problem framed around trading concepts where you had to design some functions and talk through data structures before implementing. The poster is asking what to expect in round two, which seems similar in format but longer.

Questions Asked (1)

Q1

Design a set of functions to perform specific operations, framed in a trading context. Walk through potential data structures before writing the implementation.

Algorithms & Data StructuresSystem DesignTechnical Trade-offs
Author's notes

The trading framing threw me a little at first because it sounds more domain-specific than it is.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the specific trading operations and constraints (e.g., latency, throughput, data volume). Then discuss suitable data structures, comparing trade-offs, and finally outline the implementation of the functions.

Pro tip: Emphasize the importance of low-latency and high-throughput in trading systems; mention how your choice of data structures directly impacts performance and scalability.

1. Clarify Requirements

Ask questions to understand the exact operations, expected data volumes, latency requirements, and any constraints (e.g., memory, concurrency).

2. Identify Operations

List the specific functions needed (e.g., add order, cancel order, match trades) and their expected inputs/outputs.

3. Evaluate Data Structures

Propose and compare data structures (e.g., hash maps, heaps, trees, queues) for each operation, discussing time/space complexity and trade-offs.

4. Design Functions

Outline the function signatures and high-level logic, ensuring they align with the chosen data structures and meet performance goals.

5. Discuss Implementation & Trade-offs

Walk through the implementation details, highlighting key decisions, potential bottlenecks, and how you would optimize or test.

Key Points to Mention

  • Time and space complexity of operations
  • Concurrency and thread-safety considerations
  • Use of appropriate data structures (e.g., order book as two heaps or balanced BST)
  • Handling of edge cases (e.g., partial fills, cancellations)
  • Scalability and performance under high load
  • Testing and validation strategies

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