Data Engineer - Cumberland/FICCO

Location: Chicago, IL, United States

Industry: Trading Firm

Posted: 2026-05-11

Contact: Ethan Hudson Email: ehudson@oprecruiting.com Phone: 13176505687 Data Engineer - Quantitative Trading Systems

Location: Chicago, IL (Preferred) or New York, NYAbout the Opportunity We are seeking a high-caliber Data Engineer to join a premier global proprietary trading firm. This is a critical role within a specialized team focused on developing the scalable infrastructure and high-integrity datasets that power our options and delta-one trading operations. You will work at the intersection of technology and finance, ensuring our researchers and traders have seamless, ergonomic access to the massive data volumes required for sophisticated market decision-making.

Responsibilities: Pipeline Architecture: Design, implement, and oversee robust data ingestion pipelines to onboard both vendor-supplied and internally generated datasets. Dataset Curation: Transform and manage core trading data, ensuring it is optimized for high-performance research and live execution. Quality Assurance: Develop and maintain sophisticated data control processes to identify and rectify gaps, inaccuracies, or latencies in real-time. Research Collaboration: Partner with quantitative researchers to integrate novel concepts into historical data structures and apply AI-ready annotations to diverse data streams. System Reliability: Integrate comprehensive monitoring and alerting systems to ensure the continuous health and observability of the data ecosystem.

Requirements: (must-have)

Professional Experience: At least 3 years of hands-on experience building and managing complex data pipelines in a fast-paced environment. Technical Proficiency: Deep expertise in the Python data science ecosystem and modern data engineering tools. Market Knowledge: A thorough understanding of financial derivatives, specifically options and futures, and their unique data requirements. Data Analysis: Strong mastery of financial time-series and point-in-time data analysis. Data Quality: Proven ability to engineer automated quality control frameworks for large-scale financial datasets.

Preferred Qualifications: (nice-to-have)Industry Context: Familiarity with the global financial data vendor landscape and various product offerings. Agility: Demonstrated success working in high-pressure trading environments where requirements can pivot quickly. Advanced Infrastructure: Experience developing robust APIs for streamlined data retrieval.

Base Salary: $150,000 – $200,000 (commensurate with experience and skill set).

Bonus: Eligible for an annual discretionary performance bonus.

Benefits: Comprehensive package including medical, dental, vision, 401(k) with employer match, disability, and flexible spending accounts.#LI-EH1