Senior Data Engineer

Job Summary: We are seeking a Senior Azure Data Engineer to help design, build, and operate our next-generation enterprise data platform on Microsoft Azure. You will own end-to-end delivery of data pipelines and data products that power analytics, regulatory reporting, operational dashboards, and emerging AI/ML use cases. You will partner closely with data architects, analytics engineers, data scientists, business stakeholders, and platform engineering teams to deliver reliable, performance, secure, and cost- efficient data solutions. This role is ideal for an engineer with strong hands-on depth in Azure Data Factory, Azure Synapse Analytics and/or Databricks, and modern Lakehouse patterns, who is comfortable leading migration programs (e.g., Informatica-to-ADF, on-prem warehouse-to-cloud), mentoring mid-level engineers, and shaping engineering standards across the team. Key Responsibilities: Pipeline Design & Development • Design and build robust, reusable, parameter-driven ingestion and transformation pipelines using Azure Data Factory, Synapse Pipelines, Data Bricks and/or Microsoft Fabric Data Factory. • Implement medallion architecture (Bronze / Silver / Gold) on Azure Data Lake Storage Gen2 using Delta Lake, Parquet, and structured streaming patterns. • Build performant ELT workflows that leverage pushdown to source systems (Synapse Dedicated SQL Pool, Azure SQL, Teradata) where appropriate. • Develop and optimize PySpark notebooks and jobs on Azure Databricks or Synapse Spark. Data Modeling & Warehousing • Design dimensional models (Kimball star/snowflake) and data vault patterns for analytics consumption. • Implement Slowly Changing Dimensions (Type 1/2/3), Change Data Capture, and late-arriving data patterns. • Tune distributed SQL workloads in Synapse Dedicated SQL Pool / Fabric Warehouse, including distribution keys, partitioning, and clustered column store indexes. Platform Engineering & DevOps • Implement CI/CD for data pipelines using Azure DevOps (YAML pipelines, ARM/Bicep/Terraform) across Dev / SIT / UAT / Prod environments. • Instrument pipelines with robust logging, auditing, and monitoring using Azure Monitor, Log Analytics, and KQL. • Define and enforce coding standards, code review practices, branching strategies, and release management. Migration & Modernization • Lead or contribute to legacy-to-cloud migrations — e.g., Informatica PowerCenter to Azure Data Factory, on-premises Teradata / Oracle / SQL Server to Synapse or Fabric. • Perform workload assessment, capacity planning, and cost modeling for target-state architectures. • production incident response for critical pipelines. Required Qualifications: • Deep hands-on expertise with Azure Data Factory: pipelines, datasets, linked services, triggers, parameterization, mapping data flows, and all three Integration Runtime types (Azure, Self- hosted, SSIS). • Strong Experience in Data Bricks and PySpark. • Production experience with one or more of: Azure Synapse Analytics (Dedicated and Serverless SQL Pools, Spark Pools) OR Azure Databricks (Delta Lake, Unity Catalog) OR Microsoft Fabric (Warehouse, Lakehouse, OneLake). • Strong working knowledge of Azure Data Lake Storage Gen2 (hierarchical namespace, RBAC + ACLs, lifecycle management, security). • Experience with Azure Key Vault, Azure AD / Entra ID (including managed identities and service principals), and private networking (VNet integration, private endpoints). • Monitoring and troubleshooting with Azure Monitor, Log Analytics, and KQL. • Advanced SQL — window functions, CTEs, query optimization, execution plan analysis, performance tuning. • Strong Python for data engineering — pandas, PySpark, REST API integration, unit testing (pytest). • Proficient in T-SQL; familiarity with Spark SQL, KQL, PowerShell, and Bash shell scripting. Preferred Qualifications: • 5+ years of data warehouse development experience. • 5+ years of data modeling experience using ERWIN or similar tools. • 2+ years of experience with Azure Data Factory and Snowflake. • Medicaid Domain Knowledge is a plus.