Data Engineer

ResponsibilitiesDevelop and maintain data pipelines using Azure Databricks (Python, PySpark and SQL)Implement ingestion and transformation across Bronze, Silver and Gold layers using Delta LakeSupport and operate Azure Databricks and Azure Synapse platforms, including performance monitoring and configurationBuild Gold-layer datasets optimised for Power BI and analytics consumptionSupport production workloads, resolve incidents and maintain operational documentationApply security, governance and access control standards suitable for a regulated environmentContribute to engineering standards, CI/CD pipelines and code reviewsWhat you’ll need to succeedEssentialProven experience as a Data EngineerStrong hands-on experience with AzureDatabricks, Python, PySpark and SQLExperience supporting Azure data platforms in productionUnderstanding of medallion architecture and Delta LakeDesirableExperience with Azure Synapse AnalyticsExperience with Azure Data FactoryExperience in financial services or

hands-on and implementation-focused, working within established architectural patterns to deliver reliable, secure and well-governed data for analytics, Power BI reporting and regulated finance use cases. The role also includes responsibility for supporting and maintaining underlying data platform services, including Azure Databricks and Azure Synapse.Key AccountabilitiesDelivery of reliable, scalable and well-governed data pipelines that meet business and regulatory requirementsOperational stability and performance of core data platform services including Azure Databricks and Azure SynapseAvailability of trusted, high-quality Gold-layer datasets for analytics and Power BI reportingAdherence to data security, access control and governance standards within a regulated environmentEffective resolution of data pipeline and platform incidents with clear root-cause understandingMaintenance of accurate documentation, lineage and operational run books to support ongoing platform supportKey