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Jane Street·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
May 2026

Summary

Jane Street software engineer interview with a meaty C++ streaming problem. The kind of question that sounds manageable until you're actually in it trying to keep state across batches without making a mess.

Questions Asked (1)

Q1

Given a stream of batches where each batch is a list of (timestamp, code, value) tuples sorted by timestamp then code, implement a stream transformer that emits (timestamp, row_vector) pairs. The row vector has length M (one slot per code, sorted lexicographically), and any missing code at a given timestamp should be filled with -1.

Algorithms & Data StructuresSystem DesignData Modeling
Author's notes

This one took me a while to even parse correctly.

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AI HintsAI Generated

Suggested Approach

Clarify the problem constraints first, then propose a streaming solution that maintains the lexicographically sorted list of codes and buffers incomplete timestamps. For each batch, update the code list, fill missing values with -1, and emit completed rows in timestamp order.

Pro tip: Emphasize that the code list is dynamic and must be updated as new codes appear, and that timestamps may span batches, so you need to buffer until all codes for a timestamp are seen or use a timeout/watermark.

1. Clarify Requirements and Constraints

Ask about the expected size of M, whether codes can appear later, if timestamps are strictly increasing across batches, and how to handle late data. Confirm that missing codes should be filled with -1.

2. Design Data Structures

Maintain a sorted list of codes (e.g., using a balanced BST or a sorted array with binary search) and a buffer for incomplete timestamps (e.g., a map from timestamp to a dictionary of code->value).

3. Process Each Batch

For each tuple in the batch, update the code list if a new code appears, and store the value in the buffer for that timestamp. After processing the batch, emit any timestamps that are complete (i.e., all codes present) or that are older than the current watermark.

4. Emit Row Vectors

For each emitted timestamp, construct the row vector by looking up each code in the sorted code list and using -1 if missing. Output (timestamp, row_vector) in timestamp order.

5. Handle Edge Cases and Optimize

Discuss handling of late data, memory management for large M, and potential optimizations like using a bitset for presence tracking or emitting rows with -1 for codes not yet seen.

Key Points to Mention

  • Dynamic code list: codes may appear in later batches, so the sorted list must be updated and row vectors must adapt.
  • Buffering incomplete timestamps: timestamps may span multiple batches, so you need to buffer until all codes for a timestamp are seen or use a watermark.
  • Efficient lookup: use a hash map or binary search to map codes to indices in the sorted list.
  • Memory management: consider the size of the buffer and the code list, and discuss strategies for bounded memory (e.g., emitting rows with -1 for unseen codes after a timeout).
  • Ordering guarantees: ensure output is in timestamp order, and handle out-of-order timestamps if allowed.
  • Complexity analysis: time and space complexity per batch and overall, considering M and number of codes.

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