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Design, build, and operate production-grade batch, incremental, real-time, and near-real-time data pipelines and Fabric/Azure lakehouse solutions, including data modeling, quality, monitoring, security, and legacy-platform migrations. Lead client-facing engineering workstreams, establish automated deployment and governance practices, prepare governed data for AI and RAG workloads, and mentor teams through delivery and operational handover.
8+ years in data engineering/data warehousing; 3+ years delivering Azure solutions and production
Microsoft Fabric experience
Advanced T-SQL, Spark SQL, Python/PySpark; working knowledge of KQL and DAX
Deep experience with Delta Lake, Spark tuning, medallion/lakehouse patterns, CDC and incremental loading
Strong dimensional modeling and working knowledge of Data Vault 2.0
Practical CI/CD, Git, automated testing, infrastructure as code, DataOps, governance and security experience
Support migrations from SQL Server, SSIS, SSAS, legacy warehouses and Synapse to Fabric/Azure, including conversion, reconciliation and cutover
Prepare governed data for AI/ML and RAG workloads, including ingestion, chunking, embeddings, indexing and telemetry
Lead engineering workstreams, estimates, risk management, client communication, mentoring, reusable accelerators and operational handover
Datavail is a leading provider of data management, application development, analytics, and cloud services, with more than 1,000 professionals helping clients build and manage applications and data via a world-class tech-enabled delivery platform and software solutions across all leading technologies. For more than 17 years, Datavail has worked with thousands of companies spanning different industries and sizes, and is an AWS Advanced Tier Consulting Partner, a Microsoft Solutions Partner for Data & AI and Digital & App Innovation (Azure), an Oracle Partner, and a MySQL Partner.
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