Data Engineer

• Develop and maintain scalable Python-based ETL pipelines for market data ingestion and transformation.
• Build and manage cloud data lake solutions (AWS/Databricks) for structured and unstructured data.
• Implement data quality, validation, and cleansing routines to ensure accuracy of financial time-series data.
• Optimise workflows for low latency and high throughput to support research, trading, and risk functions.
• Collaborate with portfolio managers, researchers, and traders to deliver tailored data solutions.
• Contribute to security master database design and implementation.
• Analyse and extract insights from datasets to inform trading and risk decisions.
• Document system architecture, data flows, and technical solutions.

• Bachelor's or higher in Computer Science, Engineering, Mathematics, Statistics, or a quantitative discipline.
• 5+ years developing Python-based financial software, with strong Pandas experience.
• Exposure to financial datasets across multiple asset classes.
• Experience supporting quantitative research and modelling.
• Proficiency in Linux environments.
• Strong foundation in mathematics and statistics.
• Detail-oriented, analytical, and able to thrive in a fast-paced environment.
• Excellent problem-solving and communication skills.

This is an opportunity to shape the data backbone of a sophisticated, multi-strategy investment operation while working at the cutting edge of quantitative finance.