Senior Software Engineer, Cumberland/Options Data
Posted Sep 30, 2026 · We last checked this listing on Oct 6, 2026
Likely interview questions for this role
Written from this job description, not a generic list. Each one notes what the interviewer is really checking.
About your past
Tell me about a data platform you helped scale. What broke first as volume grew?
What they are checking: Real experience with scaling limits and how they addressed them.
How do you work with traders and researchers to understand what data they actually need?
What they are checking: Turning vague requests into useful data products through good questions.
How do you mentor engineers and set standards on a data engineering team?
What they are checking: Senior-level influence on code quality and practices across the team.
What would you do
Crypto markets never close. How does that shape how you deploy and maintain data systems?
What they are checking: Operating without maintenance windows, including zero-downtime deployment and backfill strategies.
A researcher says two datasets disagree on the same trade. How do you resolve it?
What they are checking: Careful root cause investigation and clear communication about which data to trust.
About the work
The team builds datasets and APIs for crypto and options trading at large volumes. How would you design an API that serves fast queries over years of tick data?
What they are checking: Data system design focused on storage layout, indexing and access patterns for heavy time series use.
How do you guarantee data quality and integrity when ingesting from many venues at once?
What they are checking: Concrete validation, reconciliation and monitoring practices for high-volume pipelines.
How would you model options reference data so contracts across different venues map cleanly?
What they are checking: Understanding of symbology, contract specs and reference data challenges in options and crypto.
What's your approach to making pipelines idempotent and safe to rerun?
What they are checking: Defensive pipeline design that makes recovery from failures safe and simple.
What would you monitor to know your data platform is healthy?
What they are checking: Thinking in terms of freshness, completeness and latency that matter to data consumers.
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As published by DRW.