Negotiable
Undetermined
Undetermined
London Area, United Kingdom
Summary: The Senior Data Engineer role involves designing, building, and maintaining a scalable on-premise data warehouse for a Challenger Bank. The position requires strong expertise in Python, Apache Airflow, and dbt to develop robust ETL/ELT pipelines and data models. The engineer will work in a regulated environment, ensuring compliance while delivering reliable data products and visualizations. This is a long-term contract opportunity focused on infrastructure-driven data solutions.
Key Responsibilities:
- Design, build, and maintain a scalable on-premise data warehouse.
- Develop robust end-to-end ETL/ELT pipelines and curated data models.
- Utilize Python and SQL for ETL/ELT processes.
- Manage workflow orchestration and scheduling using Apache Airflow.
- Build transformation layers and testing frameworks with dbt.
- Support data warehousing, reporting, and analytics with advanced SQL and Microsoft BI stack.
- Implement CI/CD practices and test automation.
- Collaborate with cross-functional teams to translate business requirements into technical solutions.
- Deliver reliable data products and visualizations using tools like Power BI, Tableau, or Qlik.
Key Skills:
- Strong hands-on experience with Python, Apache Airflow, and dbt.
- Proficiency in SQL (T-SQL/PL-SQL) and Microsoft BI stack (SSIS, SSRS, SSAS).
- Experience in Unix/Linux environments for scripting and deployment.
- Knowledge of CI/CD practices and test automation.
- Familiarity with containerization tools such as Docker.
- Ability to work in a regulated risk and compliance framework.
Salary (Rate): undetermined
City: London Area
Country: United Kingdom
Working Arrangements: undetermined
IR35 Status: undetermined
Seniority Level: undetermined
Industry: IT
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.