Senior Software Engineer, Strategy Platform
Builds and owns platform infrastructure for data orchestration, feature computation, strategy deployment, and production trading operations at a quantitative hedge fund. Requires 5+ years in backend/data pipelines with strong debugging skills and CS degree.
About the job
Responsibilities
- Own how data is accessed, validated, orchestrated, and catalogued across research and production.
- Engineer smooth deployment processes for research experiments into production.
- Develop tooling to integrate data from diverse vendors, unifying symbol mappings for data consistency.
- Support data pipelines with strong temporal semantics under a range of latency and correctness requirements.
- Sequence platform migrations that move the firm toward shared abstractions while minimizing disruption to active trading systems.
- Lead complex projects spanning the company, collaborating across research, legal, trading, finance operations, data, and infrastructure teams.
- Build tooling to support integration with new assets and markets.
- Improve observability across the strategy lifecycle, including data cataloguing, experiment tracking, and production SLAs.
Requirements
- 5+ years of experience in backend, data pipelines, or platform engineering.
- Owned platform systems that other teams depend on daily, made real decomposition decisions (data access layers, API versioning, data models, migration sequencing), and improved those systems while they were actively in use.
- Strong debugging and observability instincts; orient quickly in unfamiliar codebases and datasets, particularly across data pipelines with many upstream sources and downstream consumers.
- Computer Science Degree, or equivalent experience.
Preferred Qualifications
- Experience with Airflow, Dagster, Spark, Iceberg, Trino, Flink, or similar data infrastructure.
- Familiarity with ML infrastructure patterns (feature stores, model serving, experiment tracking).
- Python Fluency.
Skills
Python, Airflow, Dagster, Spark, Iceberg, Trino, Flink, Data Pipelines, ML Infrastructure, Observability
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