A public-sector organisation is developing a hybrid data platform that combines an on-premises Enterprise Data Warehouse with a cloud-based Microsoft Fabric data platform. The cloud component follows a medallion architecture, while the EDW uses DataVault2.0 structures. As a senior Data Analytics Engineer, you will analyse and model data, build ETL pipelines and support Power BI reporting across diverse source systems, using SQL and dbt.
The mission
The technical landscape includes an on-premises EDW modelled with the Data Vault methodology and a cloud-based MDP. The work covers data migration across diverse source systems, source mapping, transformation and ingestion into both environments. Consistent models and traceable pipelines provide a common basis for enterprise reporting and analytics.
Your day-to-day scope spans data analysis, dimensional modelling, pipeline development, workflow orchestration, quality assurance and performance tuning. You will use dbt with SQL and Jinja, Python where appropriate, DAX for analytical logic, and Azure DevOps within an Agile delivery approach. Your work connects warehouse design and KPI definitions to Power BI semantic models and reports.
Your responsibilities
- Design and maintain robust ETL pipelines that ingest data reliably from multiple source systems into the EDW and MDP.
- Map source structures and execute data migration across diverse source systems, producing consistent and usable datasets.
- Apply DataVault2.0 and Kimball dimensional modelling to create maintainable warehouse and analytical structures.
- Develop and optimise dbt transformations with SQL and Jinja, using Python where it improves automation or maintainability.
- Define and implement relevant KPIs in Power BI datasets, reports and DAX measures based on identified reporting needs.
- Monitor data quality and pipeline performance, resolving issues through Azure DevOps and Agile delivery practices.
Your profile
Essential skills
- Bring recent, proven hands-on experience as a Power BI business analyst and Analytics Engineer, covering analysis, modelling, pipelines and reporting.
- Apply experienced Kimball dimensional modelling in an Enterprise Data Warehouse, together with DataVault2.0, data mapping and data migration for warehouse systems.
- Work fluently with SQL, dbt, Jinja and Python to build, test and maintain ETL pipelines and transformations.
- Use Microsoft Fabric and Databricks across on-premises and cloud data environments, and understand medallion architecture.
- Build Power BI reports and semantic models with DAX, and investigate which KPIs matter for particular reporting needs before implementing them.
- Work pragmatically with Azure DevOps and Agile practices, communicating clearly with technical and non-technical stakeholders.
- Hold the relevant certifications or equivalent applied knowledge, including Fabric Analytics Engineer Associate, Microsoft Power BI Data Analyst, Azure Fundamentals, Collibra Data Steward Learning Path, dbt Fundamentals and Scrum PO.
Education
- Master's degree or equivalent professional experience in a relevant discipline.