ETL Developer, Python

Job Description: You'll design and maintain the data infrastructure that powers enterprise analytics and federal reporting for some of the nation's most critical public health programs.Design, develop, and maintain enterprise ETL pipelines using Azure Data Factory (ADF), Informatica PowerCenter, and Python-based frameworks.Build and optimize scalable data processing solutions using Python, Spark, and Databricks.Support Medicaid analytics and federal reporting initiatives including T-MSIS, PERM, MARS, and Quality of Care programs.Develop robust data validation, reconciliation, and audit-traceable pipelines that hold up under regulatory scrutiny.Write and optimize SQL and stored procedures across relational platforms including Snowflake, Oracle, and SQL Server.Participate in cloud migration and modernization initiatives within Azure-based architectures, bridging legacy and modern platforms.Collaborate closely with analysts, QA engineers, and BI reporting teams to make sure data is accurate, timely, and trustworthy at every stage.Participate in code reviews, source control, and CI/CD processes using Azure DevOps and GitHub.Requirements: 5+ years of data engineering experience with a focus on enterprise data warehousing5+ years of hands-on ETL development using Informatica PowerCenter, Azure Data Factory, or comparable tools5+ years of Python development for data engineering and automation3+ years of experience with Spark-based processing frameworks (Databricks or equivalent)Strong SQL expertise and hands-on experience with relational databases including Snowflake, Oracle, or SQL ServerExperience with source control and DevOps practices (Azure DevOps, GitHub, CI/CD pipelines)Bachelor's degree or higher in Computer Science, Engineering, Analytics, or a related fieldBenefits: The work matters beyond the warehouse.The pipelines you build support Medicaid programs and federal reporting that affect millions of people.You'll be surrounded by people who care.The culture here is warm, collaborative, and grounded — people ask good questions, share what they know, and hold each other to a high standard.Your work is visible and your voice is heard.Collaborate closely with analysts, QA engineers, and BI reporting teams to make sure data is accurate, timely, and trustworthy at every stage.Follow data engineering best practices for performance, reliability, reusability, and security — not just functionality.Support production operations, incident resolution, and root-cause analysis when issues arise.