Quantitative Data Engineer

Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped our collaborative mindset, which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors.

We are looking for a Quantitative Data Engineer to join the Data Search & Analytics team. In this role, you will work with the Research and Trading desks to ensure the successful leveraging of data at the firm.

Your future role within QRT

This team is integral to the firm’s success. As such, your responsibilities will include:

• Collaborating with Quantitative Researchers and Traders to design datasets that drive systematic strategies and discretionary trading decisions.
• Working within our framework to extract, clean, and aggregate data from a wide range of raw sources and formats ensuring robust data extraction processes
• Managing end-to-end process of onboarding new datasets
• Proactively solving data related problems to minimise time to production
• Innovating and experimenting with novel data extraction methods to enhance the firm’s data onboarding toolkit

Your present skillset

• 3+ years of experience as a Data Engineer (or similar position) working with financial data; experience in a buy-side quantitative finance role is advantageous
• Rigorous about correctness: able to critically assess code and data quality, regardless of origin
• Experience using AI-powered development tools to accelerate engineering tasks and improve productivity
• Advanced programming experience in Python, including proficiency with data handling libraries such as Pandas, Polars and NumPy
• Familiarity with SQL and relational databases
• Demonstrable interest in financial markets and the application of data in its analysis and understanding
• Experience working with both traditional and alternative financial datasets
• Excellent communication skills, with the ability to effectively collaborate with all stakeholders, including researchers, traders, engineers, management, and external vendors
• Experience creating documentation and providing direct support to help stakeholders understand and use complex datasets quickly
• Ability to work in a high-performance, high-velocity environment