Senior Data Engineer

Senior Data Engineer

Build the engine behind next-generation trading analytics

This is an opportunity to work on a high-impact data platform that turns complex trading data into powerful, actionable insight.

You’ll be building a cutting-edge analytics engine used to evaluate performance, surface opportunities, and power smarter decision-making through data products, dashboards, and machine learning. This isn’t just pipeline work, it’s about shaping how data drives strategy.

You’ll join a highly collaborative team of Data Engineers, Analytics Engineers, and Data Scientists who own everything end-to-end, from infrastructure through to advanced analytics. If you enjoy working close to the problem, not just the data, this role puts you right at the centre of it.

What you’ll be doing

• Own and scale core data pipelines powering a high-performance analytics platform
• Turn complex, real-world problems into clean, efficient data models and calculations
• Design and build within a modern lakehouse/data platform architecture
• Develop APIs and data products used by internal and external stakeholders
• Bring structure to messy, real-world data through normalisation and integration
• Work with large-scale, high-volume datasets where performance matters
• Help shape how the team builds, by driving best practices in:
• Testing
• CI/CD
• Version control
• Contribute to the user-facing side of analytics, influencing how insights are delivered

What you bring

• Strong experience building cloud-based data platforms (Snowflake or similar)
• Advanced skills in Python or Rust, and SQL
• A track record of building scalable, production-grade data pipelines
• Hands-on experience with DBT and modern data transformation workflows
• Confidence working with complex, high-volume datasets
• A mindset for clean, reliable engineering with tools like:
• Docker / containerisation
• Git
• CI/CD pipelines
• Familiarity with data visualisation tools (Tableau, Power BI, or similar)

Nice to have

• Experience in trading, financial services, or data-heavy environments
• Exposure to real-time data or machine learning in production