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.
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