MS Fabric

Key Responsibilities

• Development & Delivery

Build and maintain Fabric pipelines and notebooks for ingestion and transformation across the bronze/silver/gold layers, to designs provided by the Fabric Data Lead.

Develop and maintain Lakehouse and Warehouse tables, ensuring data quality, and following agreed naming and workspace conventions.

Integrate datasets into Power BI semantic models; support and troubleshoot Direct Lake mode implementations; make agreed DAX/model changes under the model approval gate.

Work through the Code Review DevOps pipeline Deployment process.

Monitor and flag CU spikes or performance issues in own workloads; optimisenotebook/pipeline performance under guidance from the Lead.

Fix defects and production hotfixes within agreed SLAs; contribute to root-cause analysis for incidents attributable to own work.

• Governance adherence

Keep the asset catalogue, ownership register, and lineage documentation current for all assets the engineer builds or modifies.

Apply data lifecycle/retention rules, row-level security, and sensitivity labelling as defined by the governance framework, without needing to design these frameworks.

Required Experience & Qualifications

• 6 years' experience in a data engineering role.
• Minimum 1 year of hands-on Microsoft Fabric project experience.
• Solid SQL and Python/PySpark proficiency for pipeline and notebook development.
• Working knowledge of medallion (bronze/silver/gold) architecture and its practical implementation.
• Comfortable working within a defined CI/CD and code-review process.
• Relevant Microsoft certification is an advantage, not mandatory if project experience is demonstrated.

Technical Skills

• Fabric pipelines and notebooks (build/maintain)
• SQL, Python, PySpark / Spark SQL
• Lakehouse/Warehouse table development
• Power BI dataset integration and basic DA
• Azure DevOps & Git-based version control
• Understanding of medallion architecture (bronze/silver/gold)
• Exposure to Fabric capacity monitoring and remediation
• Testing framework for Data Pipelines & Notebook