Lead Market Data Engineer - Systematic Data

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
5 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.

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