Lead Data Engineer

A leading Financial Services organisation is seeking an experienced Lead Data Engineer to play a pivotal role in the continued evolution of its enterprise data platform. This is an excellent opportunity for a highly technical, hands-on engineer with deep expertise across both traditional Microsoft SQL Server technologies and modern cloud-based data engineering frameworks. The successful candidate will be instrumental in designing, developing and maintaining scalable, enterprise-grade data solutions while supporting the organisation’s ongoing transformation from legacy on-premise infrastructure to modern cloud environments. The role requires an individual who is equally comfortable working within established SQL Server ecosystems as they are leveraging contemporary orchestration, transformation and automation tooling. You will be responsible for building robust ETL and ELT pipelines using Python and SQL, orchestrating complex workflows through Apache Airflow and implementing scalable transformation logic using DBT. Working closely with technical teams and business stakeholders, you will translate complex requirements into efficient, reliable and maintainable data solutions that underpin analytics, reporting and strategic decision-making across the organisation. This environment remains highly data-centric and infrastructure-aware, making the position particularly well suited to someone who has retained strong hands-on experience with Microsoft SQL Server technologies in recent years. Advanced expertise across T-SQL, SSIS, SSRS and SSAS is essential, alongside proven experience supporting migration initiatives from legacy on-premise platforms into cloud-based architectures. The role also involves working within Unix/Linux environments for scripting, deployment and scheduling activities, as well as contributing to CI/CD processes and engineering best practices around version control, testing, monitoring and documentation. You will collaborate across cross-functional teams to ensure seamless integration of data systems while maintaining high standards of performance, governance, scalability and reliability. To be considered, candidates should demonstrate significant commercial experience within Data Engineering across complex enterprise environments. You will possess advanced Python programming capabilities for data pipelines, automation and API integrations, together with strong hands-on experience using Apache Airflow, including DAG development, orchestration and optimisation. Solid DBT expertise covering models, macros, testing and documentation is also required. Applicants must have deep SQL Server expertise with recent hands-on exposure to T-SQL, SSIS, SSRS and SSAS. Experience across ETL/ELT development, data warehousing and modern BI technologies such as Power BI, Tableau or Qlik is highly desirable. Additional exposure to Docker, CI/CD pipelines and Agile delivery methodologies would be advantageous. Previous experience within Financial Services or similarly regulated environments would be beneficial, particularly within organisations undergoing large-scale cloud migration and enterprise data transformation programmes. This is an outstanding opportunity to join a business making significant investment in its data capabilities, offering exposure to both cutting-edge cloud technologies and complex enterprise legacy systems within a collaborative, high-performing engineering environment.