Senior Data Engineer

Role Summary We are looking for a Senior Data Engineer to build and manage STACK’s data platform in Databricks. The role will develop reliable data pipelines from Finance, Delivery, Operations, HR and PMO systems, maintain high data quality and ensure that information is secure, governed and available for business use. The successful candidate will work closely with stakeholders to improve reporting, resolve data issues and support better decision-making across the organisation. Key Responsibilities Design, build and maintain data pipelines from APIs, databases, SaaS applications, files and spreadsheets into Databricks. Develop scalable data models and Delta Lake architecture for reporting, analytics and future AI use cases. Manage Databricks Workflows, Lakeflow or Delta Live Tables, SQL Warehouses and related processing jobs. Administer Databricks workspaces, Unity Catalog, permissions, service principals. Support development, test and production environments, including deployment, monitoring, incident resolution and recovery. Monitor platform performance, usage and costs, and implement appropriate security and operational controls. Implement data quality checks covering completeness, accuracy, timeliness, consistency, duplicates and reconciliation with source systems. Ensure dashboards use governed, reliable and well-documented data. Establish data ownership, common definitions, lineage, access policies and governance standards with business functions. Build monitoring and reporting to identify pipeline failures and data quality issues. Integrate governed Databricks data with Power BI and other approved analytical tools. Work with Finance, Delivery, Operations, HR and PMO to translate requirements into sustainable data solutions. Document data pipelines, controls, dependencies and operating procedures. Coordinate external partners where specialist support is required. Qualifications Significant experience as a Data Engineer, including ownership of production data pipelines. Strong hands-on experience with Databricks, Delta Lake, Python, SQL and PySpark. Experience integrating data from APIs, business applications, databases and files. Experience with Unity Catalog, access management, data governance and data quality controls. Experience administering Databricks workspaces, compute resources and SQL Warehouses. Experience with Azure data services, Power BI, Git and CI/CD practices. Understanding of environment management, monitoring, troubleshooting and cost control. Ability to work directly with non-technical stakeholders and explain data issues clearly. Strong documentation, prioritisation and problem-solving skills. Certifications (Preferred) Databricks Certified Data Engineer Professional or Databricks Certified Platform Administrator (if available).