Data Reliability Engineer
AI Summary
A Data Reliability Engineer owns and maintains critical data ETL pipelines, ensuring reliability and data quality to support trading and investment decisions in a fast-paced systematic trading environment.
About this role
A Career with Cubist
Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures, and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources.
What You’ll Do
We are passionate about data. We collaborate to build elegant, effective, scalable, and highly reliable solutions to empower predictive modeling in finance.
You will join a team that plays a vital role in ensuring the smooth day-to-day implementation of a large research infrastructure and the timely delivery of comprehensive and error-free data to Cubist’s portfolio managers across the globe. Specifically, you will:
- Serve as a frontline owner for thousands of mission-critical data ETL pipelines that power trading and investment decision-making, ensuring reliability, accuracy, and timeliness.
- Actively manage and resolve data incidents in a fast-paced trading environment, partnering closely with portfolio managers, data scientists, and external data vendors.
- Design and build tooling, automation, and robust documentation to improve operational efficiency, scalability, and data quality across the platform.
- Play a hands-on role in daily data operations, including data validation, remediation, and enrichment, with opportunities to continuously improve and modernize workflows through engineering best practices.
What’s Required
- Bachelor’s degree with a focus in computer science or a related field.
- Strong proficiency in SQL Server and Python programming, with experience in AWS and both Windows and Linux environments; familiarity with Databricks is a plus.
- Exceptional attention to detail with a strong appreciation for well-defined processes and systems.
- 3+ years of experience in a client-facing support or operations role.
- Excellent organizational, communication, and interpersonal skills.
- Demonstrated commitment to the highest ethical standards.
Skills
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