What You'll Do

• Build and maintain end-to-end data pipelines to ingest, process and transform vendor and exchange data into research-ready datasets.
• Onboard new data sources and develop derived datasets to support quantitative research.
• Manage and optimise databases and storage systems for query performance and cost efficiency.
• Improve data quality through automated validation, cleaning, monitoring and production alerting.
• Document data sources, structures and usage to help research teams work effectively with the data.

What We're Looking For

• 3+ years of experience building and maintaining production data pipelines, with flexibility for more senior candidates who remain hands-on.
• Strong Python programming skills and the ability to write clean, reliable and maintainable code.
• Experience in one or more areas of data engineering, such as data ingestion, transformation, pipeline development, storage or query optimisation.
• A practical problem-solving mindset, strong learning agility and the ability to adapt to new tools and technologies.
• Good written and verbal English communication skills.

Nice to Have

• Experience with financial market data, exchange feeds, securities data or crypto data streams.
• Background in quantitative finance, hedge funds, fintech or other data-intensive environments.
• Familiarity with Snowflake, ClickHouse, PySpark or similar data technologies.

Why Consider This Opportunity?

You'll have the opportunity to take ownership of data engineering work, improve existing data workflows and help build the data foundation supporting quantitative investment activities.