Senior Engineer, Systematic Data

priorities, You are highly collaborative and will build strong working relationships within our team and with our stakeholders. You are naturally curious, analytical in your approach to problems and able to deal positively with conflicting views. You are constantly looking for opportunities to further accelerate alpha discovery, reduce time to market and improve operational scale/stability through enhancements to our platform and processes, and through ensuring optimal alignment and integration with the systematic research process. REQUIREMENTS: Essential Degree in Computer Science or a related field with computational focus 7+ years of hands-on development experience building and supporting production systems Highly skilled in Python, comfortable with different programming styles (e.g. OO, functional) and strong on design patterns Strong understanding of system architecture and the full technology stack (software, OS, CPU/memory, local/network storage, networking, etc.) Proponent of collaborative software development approaches: version control, CI/CD, automated testing, code review, refactoring, and related approaches Craftsman-like approach to building software, taking pride in clean and efficient code, and instilling these values in others Strong knowledge of one or more relevant database technologies (e.g. Postgres/MSSQL, Redshift/Snowflake, KDB/OneTick) Solid understanding of time-series data and temporal queries Linux platforms and related scripting Understanding of financial markets and instruments (particularly cash equities) Experience in a front office trading environment (e.g. hedge fund or investment bank) - ideally systematic/quantitative in nature Beneficial Proficient in one or more OO programming languages (e.g. Java/C#) Experience with datasets used for cash equity research and trading Experience with distributed computing (e.g. Spark/Dask, Slurm/HTCondor) Experience with event-driven, asynchronous architectures and related messaging technologies (e.g. Kafka, MQ) Experience with cloud platforms (e.g. AWS, GCP, Azure) Experience with orchestration and container technologies (e.g. Airflow, Kubernetes, Docker) Experience with monitoring and alerting tools (e.g. CloudWatch, Prometheus, Grafana, Sentry/OTel)