ETL/Data Engineer
On-site · Indianapolis, Indiana, United States
Job Summary
Senior Azure Data Engineer to design, build, and operate Vergence's next-generation enterprise data platform on Microsoft Azure. Own end-to-end delivery of data pipelines and data products powering analytics, regulatory reporting, operational dashboards, and emerging AI/ML use cases. Partner with data architects, analytics engineers, data scientists, business stakeholders, and platform engineering teams to deliver reliable, performant, secure, and cost-efficient data solutions. Focus on Azure Data Factory, Azure Synapse Analytics and/or Azure Databricks, modern Lakehouse patterns, migration programs (e.g., Informatica-to-ADF, on-prem warehouse-to-cloud), mentoring mid-level engineers, and shaping engineering standards across the team.
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, Selfhosted, 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 (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.
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