Seeking a seasoned Senior Consultant to spearhead Microsoft Azure and Microsoft Fabric data modernization and migration initiatives. This role involves leading the end-to-end design, development, and deployment of scalable data solutions. You will be instrumental in guiding clients through complex data transformations, leveraging cutting-edge Azure services and the unified Fabric platform. This is an excellent opportunity for an expert to make a significant impact on client success and drive technical excellence.

The position requires a deep understanding of modern data architectures, including Lakehouse and Warehouse concepts, and the ability to translate business needs into robust technical designs. You will also be responsible for establishing best practices in code development, testing, and deployment, ensuring high-quality, maintainable solutions. Collaboration across teams and mentorship of junior engineers are key components of this role.

Lead the complete lifecycle of Microsoft Fabric and Azure data engineering solution delivery. Convert business requirements into scalable technical architectures, defining Lakehouse, Warehouse, and data ingestion strategies. Establish and enforce coding standards for notebooks, pipelines, and SQL development. Optimize Fabric performance, Spark processing, and SQL workloads. Design and implement secure access patterns using Microsoft Entra ID and other cloud security features. Drive CI/CD practices and manage deployments effectively. Conduct code reviews, troubleshoot issues, and mentor junior engineers. Guide clients in migrating from existing data platforms to Microsoft Fabric. Produce comprehensive documentation, including solution designs and operational runbooks.

Requires strong hands-on expertise in Azure data engineering and Microsoft Fabric, coupled with advanced SQL, Python, and PySpark skills. Proven experience with Lakehouse, One Lake, Delta Lake, Data Factory, Fabric Warehouse, and Power BI integration is essential. A solid grasp of distributed processing and Spark optimization is critical. Experience with metadata-driven processing, dimensional modeling, and data warehousing is mandatory. Must have a background in CI/CD, Git, release management, and Infrastructure as Code. Proficiency in cloud security, network controls, data governance, and access management is required. The ability to estimate work, identify risks, and lead technical teams is also necessary.