A technology-driven investment firm is hiring a Quantitative Data Engineer to help design and operate the data systems that underpin research and trading across global markets.
This role sits at the intersection of data engineering, quantitative research, and production trading systems . You’ll focus on building robust, high-performance data pipelines and analytical frameworks that support model development, signal research, and live trading workflows.
Role Focus
You will work directly with researchers, quantitative analysts, and engineers to translate complex research requirements into scalable data solutions. The position emphasizes Python-based data engineering, structured data modeling, and production reliability in a research-driven environment.
Key Responsibilities
• Analyze research and trading workflows to design data pipelines that support quantitative modeling and time-series analysis
• Build, test, and optimize Python-based data systems used in research and production environments
• Develop reusable data frameworks, libraries, and services that improve researcher efficiency and data quality
• Partner with engineering and research teams to evolve data platforms as strategies and models change
• Own production data workflows, including monitoring, troubleshooting, and incident resolution
• Produce clear technical documentation covering system design, data contracts, and operational procedures
Technical Profile
• Bachelor’s degree in a technical discipline such as computer science, engineering, or a related field
• Strong Python development experience, including heavy use of numerical and data libraries
• Solid SQL skills and experience working with large, structured datasets
• Hands-on experience with relational or NoSQL database systems
• Familiarity with workflow orchestration, containerization, or distributed systems is a plus
• Strong debugging, performance optimization, and systems-level problem-solving skills
• Ability to reason analytically about data quality, latency, and reliability
• Comfortable communicating technical concepts across engineering and research audiences
