Data Engineer - Financial services

If you want to work in an environment where you can innovate, automate, and shape how data is used across the business, this role gives you the freedom to do exactly that. You'll collaborate with a highly skilled team to design and deliver end?to?end cloud data solutions, bringing together engineering best practice, automation, and customer?centric thinking. If you're driven by clean architecture, reliable pipelines, and meaningful outcomes, you'll feel right at home here.

What you'll be doing:

• Work with the business in designing and delivering data-driven products and promoting a data-driven culture
• Work to build scalable data engineering solutions that can move data between systems/platforms, these could be real-time, event driven or batch runs.
• Build and maintain reference data for teams to have essential lookups enabling the understanding of data definitions and version controls.
• Development of tools that enable clients to interface with their data for purposes such as analysis and data visualisation.
• Work with Engineers to develop data solutions
• Collaborate with Business to productionise and deploy models
• Build Data Pipelines for Regulatory reporting
• Design cloud infrastructure solutions

What you offer:

• 5+ years' experience in Data Engineering or Python backend development, or strong interest in transitioning into Data Engineering
• Strong Python expertise, with hands on experience across backend and data engineering
• Proven experience working with modern data platforms, including cloud data lakes, Apache Iceberg, Airflow and dbt
• Demonstrated ability to design, build and maintain scalable backend services and APIs
• Experience developing robust data pipelines for both structured and unstructured data
• Solid background in microservices architecture, with a focus on Kubernetes and CI/CD best practices
• Good understanding of cloud native environments and integrating data and security tooling
• Commitment to high quality, reliable code through testing, automation and engineering best practices.