Credit Data Engineer

This range is provided by Selby Jennings. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

$/yr - $/yr

The firm is seeking a Data Engineer to join its Global Data Engineering group in New York. This role will concentrate on supporting the Credit Trading team and enhancing ETF and portfolio‑driven systematic strategies. The position involves designing and maintaining data solutions that enable both real‑time trading and long‑term research, covering the full data lifecycle—from initial discovery to transformation and validation—for datasets used in production and research environments.

• Build advanced analytics and frameworks to assess trade‑offs among return sources, market flow, and risk.
• Partner with quantitative research teams and market data specialists to identify market drivers and inform trading decisions.
• Structure and normalize complex financial datasets to ensure they are accurate, well‑organized, and optimized for research and trading systems.
• Guarantee the reliability and performance of datasets and related APIs.
• Work closely with researchers and engineers to anticipate evolving data needs and deliver scalable, dependable solutions.
• Maintain high standards of data quality through validation, monitoring, and robust engineering practices.

• Collaboration with leading professionals from more than 40 countries.
• Competitive compensation and benefits.
• Participation in a global profit‑sharing pool and performance‑based bonuses.
• 401(k) matching up to 50%.
• Comprehensive health, dental, vision, mental health, disability, and life insurance coverage.
• 25 paid vacation days plus market holidays.
• Office perks including meals, snacks, social events, clubs, and sports leagues.

• 3+ years of experience as a Data Engineer, Data Scientist, or similar role in a high‑performance setting, preferably within financial services.
• Strong Python skills, including experience with libraries such as Pandas, Arrow, and Spark.
• Expertise in data modeling, normalization, and API development for large‑scale analytical or trading systems.
• Experience with lakehouse architectures (e.g., Delta Lake, Databricks, AWS) for managing large analytical datasets.
• Familiarity with data sources relevant to Fixed Income trading, such as CDS, corporate structures, and bond NAVs.
• Solid software engineering fundamentals, particularly in performance, scalability, and reliability for distributed systems.
• Knowledge of statistical models and quantitative finance methods.
• Exceptional attention to detail, organizational skills, and project management capabilities.
• Ability to thrive in a fast‑paced, collaborative environment.
• Must have legal authorization to work in the U.S.; sponsorship is not available for this role.