Internship, Data Engineering

Your future role at QRT  

As part of QRT’s data teams, you’ll work on the systems and datasets behind quantitative research and trading. You’ll collaborate closely with traders, researchers and engineers, tackling problems across data acquisition, engineering and platform design. 

Throughout the recruitment process, we’ll consider your skills and interests alongside the problems our teams are working on. Depending on the strongest fit, your internship may focus on one of the following areas: 

• Quantitative Data Analyst – Source and evaluate new datasets based on priorities from our trading desks. You’ll explore how new data can support research, manage sourcing projects from acquisition through to design, and work with Data Engineers to bring useful datasets into production at scale. 
• Data Engineer – Work with large datasets across QRT’s research and trading platforms. You’ll design and implement data stores and APIs, monitor data processes and build production-ready datasets that researchers and traders can use effectively. 
• Data Platform Engineer – Build and maintain the infrastructure used to ingest, process and serve data across our research environment. You’ll work on real-time and batch workflows, with a focus on reliability, latency and efficiently handling growing volumes of complex data. 

Your present skillset 

• Computer science foundations – A good grounding in areas such as algorithms, data structures, parallel programming and object-oriented programming. 
• Programming – Experience with Python and an interest in using software to solve data or infrastructure problems. 
• Engineering interests – An interest in software engineering, infrastructure or data engineering, particularly where performance and reliability matter. 
• Systems – Curious about high-performance, real-time systems and interested in developing a deeper understanding of how they support trading. 
• Problem solving – A rigorous, structured approach to analysing unfamiliar problems and working towards practical solutions. 
• Communication – Able to communicate clearly and collaborate directly with researchers, traders and engineers. 
• Approach – Self-motivated and keen to develop autonomy as you learn. 

Preferred qualifications (a plus): 

• Knowledge of SQL or NoSQL databases. 
• Experience with front-end development. 
• An interest in financial markets and/or algorithmic trading.