What are the responsibilities and job description for the Lead Market Data Engineer - Systematic Data position at Balyasny Asset Management L.P.?
The Lead Market Data Engineer will architect, build, and optimize the platforms that deliver high-quality market data to fuel quantitative research and systematic trading strategies. This hands-on leader will collaborate with researchers, technologists, and trading teams to ensure the seamless integration of deep historical datasets and real-time, low-latency feeds across global markets and asset classes. The ideal candidate combines technical excellence, systematic trading experience, and a nuanced understanding of global market data infrastructure. This role is critical to powering alpha generation and robust execution for the firm’s multi-asset, systematic trading business.
Key Responsibilities
- Design, implement, and maintain scalable market data pipelines for both historical and real-time data across equities, futures, FX, and other asset classes.
- Lead the engineering efforts to support systematic research and low-latency trading, ensuring data quality, reliability, and minimal latency.
- Collaborate with quantitative researchers, portfolio managers, and technology teams to deliver data solutions that drive alpha and execution performance.
- Oversee the ingestion, normalization, and distribution of market data from global exchanges and vendors, addressing region-specific and asset-class-specific challenges.
- Evaluate and integrate new data sources, technologies, and protocols to maintain a competitive edge in data-driven trading.
- Establish and enforce best practices for data governance, compliance, and security in a regulated environment.
- Troubleshoot and resolve complex data issues impacting research or trading in real time.
- Contribute to the strategic direction of the firm’s data architecture and technology stack.
Requirements
- 10 years of experience in market data engineering at a leading quantitative trading firm, hedge fund, or proprietary trading shop.
- Deep expertise in building and maintaining market data systems for both historical research and real-time trading.
- Strong programming skills in languages such as Python, C , or Java, with experience in distributed systems and low-latency architectures.
- Demonstrated experience supporting systematic trading strategies and quantitative research workflows.
- In-depth knowledge of global market data protocols, exchange feeds, and vendor APIs.
- Analytical mindset with the ability to diagnose and resolve complex data and performance issues.
- Experience with cloud-native architectures, containerization, and modern DevOps practices.
- Excellent communication and stakeholder management skills.
- Bachelor’s or advanced degree in Computer Science, Engineering, Mathematics, or a related field.
Preferred Qualifications
- Experience with ultra-low-latency data delivery and high-frequency trading environments.
- Familiarity with global market structure, regulatory requirements, and region-specific data challenges.
- Prior experience integrating alternative data sources and advanced analytics into trading workflows.
- Contributions to open-source market data projects or recognized thought leadership in the field.
- Advanced degree (MS/PhD) in a technical or quantitative discipline.