← Jane Street Interview Insights
I started with the obvious outbound stuff: new order, cancel, cancel-replace.
Start by outlining the high-level message flows between the trading system and exchange, then detail the key fields for each message type. Emphasize reliability, latency, and data integrity considerations.
Pro tip: Highlight the importance of idempotent message handling and sequence numbers to handle duplicates and out-of-order messages, which is critical in high-frequency trading environments.
List the message types initiated by the trading system, such as order submissions, cancellations, and modifications. For each, specify the essential fields like order ID, symbol, side, quantity, price, and time-in-force.
List the message types sent by the exchange, including order acknowledgments, executions, cancellations, and market data updates. Include key fields such as order ID, execution ID, fill quantity, price, and timestamps.
For each message, detail the mandatory and optional fields, ensuring they support identification, routing, and processing. Consider fields like client order ID, exchange order ID, symbol, side, price, quantity, and timestamps.
Discuss mechanisms like sequence numbers, checksums, and acknowledgments to ensure message integrity and order. Mention how to handle rejects, partial fills, and connection drops.
Mention low-latency protocols (e.g., FIX, binary), batching, and compression. Highlight the need for high throughput and minimal latency in trading systems.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
This is where I spent the most time and also where I got the most pushback.
Start by clarifying the system's constraints (e.g., message broker, order volume, latency requirements) and then propose a layered approach: idempotent producers/consumers, ordering via partition keys, and effectively-once through deduplication and transactional offsets. Emphasize trade-offs between strict guarantees and performance, and how you would validate with testing and monitoring.
Pro tip: Interviewers at Jane Street value pragmatic reasoning over buzzwords—acknowledge that true exactly-once is impossible end-to-end, so focus on achieving effectively-once via idempotency and deduplication, and discuss how you'd handle edge cases like broker failures or duplicate messages.
Ask about the message broker (Kafka, RabbitMQ, etc.), expected throughput, latency tolerance, and whether ordering is global or per-order. This shows you tailor solutions to context.
Use unique message IDs and idempotent consumers that check a deduplication store (e.g., Redis, database) before processing. For producers, enable idempotent writes if supported (e.g., Kafka's idempotent producer).
Partition messages by order ID (or a key) so that all messages for a given order go to the same partition and are processed in order. Discuss how to handle out-of-order messages if partitioning isn't possible.
Combine idempotency with transactional offsets (e.g., Kafka transactions) or two-phase commit to atomically update state and commit offsets. Alternatively, use a deduplication table with unique constraints.
Discuss how to handle broker failures, consumer crashes, and network partitions. Propose monitoring for duplicates, ordering violations, and lag, and describe testing strategies like chaos engineering.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
FIX protocol experience actually helped me here, though I tried not to just recite FIX because that felt like a cop-out.
Start by clarifying the requirements and constraints (e.g., latency, reliability, exchange protocol) to show you understand the problem space. Then walk through the lifecycle of a session: establishment, maintenance (heartbeats, sequence numbers), error handling (resend requests), and recovery (reconnect logic). Emphasize trade-offs and how you would test and monitor the system.
Pro tip: Demonstrate awareness of real-world exchange protocols (e.g., FIX, OUCH) and the importance of idempotency and exactly-once semantics in trading systems. Mention that you would design for graceful degradation and observability from the start.
Ask about expected message rates, latency requirements, exchange protocol specifics, and failure modes. This shows you don't jump to solutions without understanding the problem.
Describe how to initiate a session (e.g., logon handshake) and maintain it with periodic heartbeats. Explain how missed heartbeats trigger a reconnect.
Explain the use of monotonically increasing sequence numbers for both inbound and outbound messages. Describe how to detect gaps and request resends.
Detail the process for requesting missing messages, handling duplicates, and ensuring state consistency. Mention the importance of idempotent processing.
Outline the steps after a disconnect: re-establish connection, replay missed messages, reconcile local state with exchange, and resume normal operation. Discuss backoff strategies and failover.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Start by acknowledging that failures are inevitable in exchange connectivity and must be designed for explicitly. Then walk through each failure mode (timeouts, duplicates, partial fills) by explaining detection, mitigation, and recovery strategies, emphasizing idempotency and reconciliation. Finally, tie it back to system-level trade-offs like latency vs. consistency and how you'd validate the design.
Pro tip: Frame failure handling as a first-class design concern, not an afterthought—mention that you'd build a deterministic state machine with sequence numbers and idempotent message processing, and that you'd test with chaos engineering. This shows you think about production reliability, which is critical in trading systems.
Enumerate timeouts, duplicate messages, and partial fills, and explain how each can lead to inconsistent state or financial loss. Highlight the need for detection mechanisms like heartbeats, sequence gaps, and order status queries.
Describe using unique message IDs, sequence numbers, and deduplication caches to ensure duplicate messages are safely ignored. Emphasize that all operations should be idempotent so retries don't cause double execution.
Explain how to set timeouts based on expected latency, use exponential backoff with jitter for retries, and avoid retry storms. Mention that timeouts should trigger reconciliation rather than blind retries for non-idempotent operations.
Discuss tracking order state with a state machine, handling partial fills by updating remaining quantity, and periodically reconciling with the exchange via order status requests to detect and resolve discrepancies.
Propose unit tests for edge cases, integration tests with simulated failures, and chaos engineering in staging. Mention monitoring for latency, error rates, and reconciliation mismatches to catch issues early.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.