Senior Microsoft Fabric Data Engineer - Manager - Data & AI - Technology Consulting - Advisory

As a Senior Microsoft Fabric Data Engineer, you will play a key role in designing, developing, and delivering enterprise-grade data platforms on Microsoft Fabric. You will be responsible for the end-to-end implementation of data engineering solutions, from data ingestion and transformation through to analytics enablement, governance, and operational support.

Working closely with Solution Architects, Business Stakeholders, Data Analysts, and AI teams, you will translate business requirements into scalable, secure, and high-performing data solutions that support reporting, advanced analytics, and AI-driven use cases.

This is a highly hands-on role requiring deep expertise across the Microsoft Fabric ecosystem, including OneLake, Lakehouse, Data Warehouse, Data Factory, Dataflows Gen2, Real-Time Intelligence, Power BI, Semantic Models, and Microsoft Purview. The candidate will take ownership of data engineering workstreams and contribute to the development of reusable frameworks, best practices, and delivery accelerators that improve solution quality and delivery efficiency.

What You Will Do

• Design, develop, deploy, and support enterprise-scale Microsoft Fabric solutions across Data Engineering, Analytics, and AI initiatives.
• Design and maintain scalable Lakehouse, Warehouse, and Medallion Architecture patterns within Microsoft Fabric.
• Build and optimise data ingestion frameworks using Fabric Data Factory, Dataflows Gen2, Fabric Mirroring, shortcuts, APIs, databases, SaaS applications, and cloud-native data sources.
• Develop reusable ingestion patterns and accelerators to support rapid and consistent project delivery.
• Integrate structured, semi-structured, and streaming data into Microsoft Fabric OneLake.
• Develop and optimise Spark, PySpark, and SQL-based transformation pipelines.
• Build scalable ETL/ELT frameworks supporting enterprise reporting, analytics, and AI workloads.
• Design and implement real-time analytics solutions using Eventstreams, Real-Time Intelligence, and streaming data architectures where appropriate.
• Enable AI-ready data foundations supporting Copilot, Fabric Data Agents, Machine Learning, and Generative AI workloads.
• Implement data quality controls, validation frameworks, monitoring processes, and automated alerting mechanisms.
• Implement data governance standards, metadata management, lineage, and security controls using Microsoft Purview and Microsoft Fabric governance capabilities.
• Support the development of trusted, governed, secure, and compliant data platforms.
• Establish CI/CD pipelines, source control standards, testing frameworks, and automated deployment processes using Azure DevOps and Git.
• Develop reusable templates, accelerators, and engineering frameworks to improve delivery quality, consistency, and productivity.
• Monitor platform performance, optimise workloads, and troubleshoot complex data engineering issues.
• Collaborate with Solution Architects, Business Stakeholders, Data Analysts, and AI teams to deliver successful business outcomes.
• Support the implementation of modern analytics, AI, and self-service reporting solutions leveraging the Microsoft Fabric ecosystem.
• Take ownership of end-to-end delivery of data engineering workstreams, ensuring solutions are delivered to agreed quality, governance, security, and performance standards.

• 6+ years' experience in Data Engineering and Azure Analytics platforms.
• Demonstrated experience delivering modern Azure Data & Analytics solutions, including hands-on Microsoft Fabric implementations in production environments.
• Strong hands-on experience with Fabric Lakehouse, Fabric Warehouse, OneLake, Data Factory, Dataflows Gen2, Notebooks, and Semantic Models.
• Extensive experience building scalable ETL/ELT solutions and modern data platforms.
• Strong expertise in SQL, Python, PySpark, and data modelling principles.
• Experience implementing Medallion Architecture, Delta Lake, and modern analytics patterns.
• Experience integrating data from APIs, SaaS platforms, databases, and cloud-based systems.
• Strong understanding of data governance, security, metadata management, and compliance practices.
• Experience implementing CI/CD pipelines, source control, and DevOps engineering practices.
• Proven ability to troubleshoot, optimise, and support enterprise-scale data platforms.
• Strong communication and stakeholder management skills with experience working across technical and business teams.
• Experience collaborating with Solution Architects, Data Analysts, and engineering teams to deliver complex data platform solutions