About the Opportunity
Our client, a leading multi-strategy investment firm, is seeking a Senior Data Developer located in New York City or London to join its core data engineering team, bridging the worlds of software development, analytics, and market data infrastructure. This hybrid role will help design, build, and maintain a modern data platform that supports quantitative research, trading, and risk-management initiatives across multiple asset classes. The ideal candidate will take ownership of end-to-end data pipelines, develop robust market data solutions, and partner closely with quantitative and investment professionals to ensure timely and accurate access to mission-critical data.
The annual base salary range is $150,000 to $220,000. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things. Details about eligibility for bonus compensation (if applicable) will be finalized at the time of offer.
Job Responsibilities
- Design, develop, and optimize Python-based ETL workflows to process large volumes of structured and unstructured financial data
- Build and operate cloud-based data lake solutions (e.g., AWS, Databricks) to support high-frequency trading, analytics, and risk systems
- Implement strong data quality, validation, and cleansing frameworks to ensure data integrity across the organization
- Enhance and maintain the firm’s security master and reference data systems
- Collaborate with portfolio managers, researchers, and technology teams to deliver data solutions that drive investment performance
- Document data architecture, processes, and technical workflows for ongoing scalability and transparency
Job Requirements
- Bachelor’s or advanced degree in Computer Science, Engineering, Mathematics, or a related quantitative field
- 5+ years of experience developing financial or trading applications in Python
- Strong command of Pandas, Linux environments, and distributed data systems
- Familiarity with financial datasets spanning multiple asset classes
- Demonstrated ability to partner with quantitative teams to support research and modeling
- Exceptional analytical, problem-solving, and communication skills
- Comfortable working in a fast-paced, collaborative environment
Preferred Skills
- Exposure to Kafka or streaming technologies
- Understanding of financial market data, symbology, and reference data across equities, futures, and OTC products
- Prior experience in a hedge fund, proprietary trading, or quantitative finance setting
- Knowledge of cloud platforms (AWS or Azure)
- Familiarity with LLM/AI architectures and integrating ML models into data pipelines
