Credit Data Engineer

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.

Core Responsibilities

• 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.

What's Offered

• 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.

Ideal Candidate

• 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.