Senior Data Engineer

Datavail is hiring a Senior Data Engineer to design, build, and maintain production-grade data pipelines and solutions across Microsoft Fabric and Azure. The role also leads client-facing engineering work, migrations, governance, AI/ML data preparation, and operational delivery.

Responsibilities:

• Design, build and maintain production-grade batch, incremental, real-time and near-real-time data pipelines across Microsoft Fabric and Azure
• Implement CDC, watermarking, merge/upsert, late-arriving-data and idempotent reprocessing patterns
• Develop PySpark, Spark SQL and T-SQL transformations across bronze, silver and gold Delta Lake layers
• Build Fabric solutions using OneLake, Lakehouse, Warehouse, Data Factory, Dataflows Gen2, Spark notebooks, Real-Time Intelligence and Power BI
• Implement dimensional and Data Vault models, data-quality testing, reconciliation, observability, logging, alerting and SLA monitoring
• Establish Git-based CI/CD and automated deployment using Azure DevOps or GitHub, Fabric deployment pipelines, REST APIs, Bicep and Terraform
• Apply Purview catalog/lineage, least-privilege access, sensitivity controls, encryption and secure connectivity
• 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

Requirements:

• 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
• Professional-services/client-facing delivery experience
• Authorization to work in the US
• Design, build and maintain production-grade batch, incremental, real-time and near-real-time data pipelines across Microsoft Fabric and Azure
• Implement CDC, watermarking, merge/upsert, late-arriving-data and idempotent reprocessing patterns
• Develop PySpark, Spark SQL and T-SQL transformations across bronze, silver and gold Delta Lake layers
• Build Fabric solutions using OneLake, Lakehouse, Warehouse, Data Factory, Dataflows Gen2, Spark notebooks, Real-Time Intelligence and Power BI
• Implement dimensional and Data Vault models, data-quality testing, reconciliation, observability, logging, alerting and SLA monitoring
• Establish Git-based CI/CD and automated deployment using Azure DevOps or GitHub, Fabric deployment pipelines, REST APIs, Bicep and Terraform
• Apply Purview catalog/lineage, least-privilege access, sensitivity controls, encryption and secure connectivity
• 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
• DP-700, DP-600, DP-203
• streaming/event-driven, RAG/GenAI, Fabric IQ/data agents, and industry experience