We are recruiting a Senior Data Engineer on a long-term contract basis for a Challenger Bank, responsible for designing, building and maintaining a scalable on-premise data warehouse using modern data engineering practices. This role sits in a non-cloud environment and requires strong ownership of infrastructure-focused data solutions, delivering robust end-to-end ETL/ELT pipelines and curated data models to support analytics and reporting.
This position requires strong hands-on experience with Python, Apache Airflow and dbt as essential skills, as these will be central to building, orchestrating and transforming the bank’s data pipelines. You will use Python and SQL to develop ETL/ELT processes, Apache Airflow to design and manage workflow orchestration and scheduling, and dbt to build scalable transformation layers, data models and testing frameworks (including medallion architecture where applicable). Strong experience working in Unix/Linux environments is also key for scripting, deployment and operational support.
In addition, you will work with advanced SQL (T-SQL/PL-SQL) and the Microsoft BI stack (SSIS, SSRS, SSAS), supporting data warehousing, reporting and analytics capabilities. The role also involves CI/CD practices, test automation, and exposure to containerisation tools such as Docker.
You will collaborate with cross-functional teams to translate business requirements into technical solutions and deliver reliable data products and visualisations using tools such as Power BI, Tableau or Qlik.
This is a long-term contract opportunity for a hands-on Data Engineer who is comfortable working in an on-premise banking environment, taking ownership of the full data lifecycle from ingestion through to analytics-ready datasets while operating within a regulated risk and compliance framework.