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This role involves close collaboration with quantitative researchers across execution strategy, research, and trading to build scalable systems for processing both structured and unstructured data from a wide range of sources. You’ll develop automated analytics solutions that integrate advanced statistical techniques and modern technologies to support trading strategies and research workflows.
Key Responsibilities
- Manage and maintain multiple datasets, each with distinct structures and update frequencies
- Work alongside researchers to deliver both raw and enriched data sets, as well as supporting analytics
- Design, automate, and maintain robust data pipelines tailored to research and trading needs
- Set up infrastructure for data exploration, visualization, and interactive analytics
- Build and deploy large-scale applications in a cloud environment
Responsibilities
- Ownership of several datasets each with its own unique schema and delivery frequency
- Partner with researchers to produce high-value raw dataset as well as analytics
- Design, create, automate, and maintain custom data pipelines
- Setup analytical infrastructure to facilitate exploration and visualization of datasets
- Large scale cloud development of applications as a service
Skills & Qualifications
- Proven experience in data engineering with measurable business impact
- Strong skills in data manipulation, query design, and performance optimization
- Proficiency in Python, SQL, and software packaging; familiarity with KDB+/q is a plus
- Experience in areas such as distributed systems, machine learning, platform engineering, networking, systems design, or web development
- Strong quantitative and analytical thinking
- Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, or a closely related field
