Senior Data Engineer Databricks, Azure & People Analytics - 20184

About this job

Job Overview Assignment Description We are looking for a Senior Data Engineer to develop and enhance a modern, scalable data platform supporting HR and People Analytics. The role focuses on data integration, advanced data modelling, data quality, governance, and analytics. You will build reliable data pipelines and reusable, quality-assured datasets that support reporting, advanced analysis, and self-service analytics while ensuring data security and GDPR compliance. What You Will Work On Design and develop dimensional and semantic data models, including star schemas and Slowly Changing Dimensions (SCD). Build and maintain Bronze, Silver, and Gold data layers. Develop and optimise ETL/ELT pipelines using Databricks, Azure Data Factory, SQL, Python, and PySpark. Work with Delta Lake, Lakeflow, and Unity Catalog. Implement automated testing, data validation, profiling, and quality monitoring. Optimise pipeline performance, incremental processing, and storage costs. Implement data governance, access controls, and GDPR-compliant data protection. Create reusable, version-controlled datasets with clear definitions, documentation, and traceability. Translate business requirements into robust technical solutions in collaboration with stakeholders and development teams. Collaborate with Power BI developers to optimise analytical models. Contribute to CI/CD, release management, incident management, and technical documentation. What You Bring Extensive hands-on experience with Databricks Lakehouse, Delta Lake, Lakeflow, and Unity Catalog. Strong experience with Azure Data Factory, SQL, Python/PySpark, and large-scale data pipelines. Expertise in dimensional and semantic data modelling, including SCD, role-playing dimensions, and calculation groups. Experience modelling HR and business data from Workday, Peakon, or equivalent HCM, employee experience, or financial systems. Experience with automated testing, data validation, data profiling, and data quality monitoring. Knowledge of row-level and column-level security, personal data protection, data retention policies, and GDPR controls. Ability to translate business requirements into scalable technical solutions. Strong analytical, communication, and stakeholder collaboration skills.

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