Senior Data Engineer – Python ETL (Data Quality, Spark/Databricks)

Senior Data Engineer – Python ETL (Data Quality, Spark/Databricks) Remote - US Based 12+ Month Contract Not Open to Third Party Firms We are seeking a hands-on Senior Data Engineer (ETL / Python Developer) to support an enterprise data warehouse and analytics program within a regulated healthcare environment. This role focuses on designing, building, and modernizing large-scale data ingestion and transformation pipelines that support analytics, reporting, and compliance-driven data initiatives. The ideal candidate has strong Python-based data engineering experience and deep exposure to enterprise ETL environments, including legacy modernization and cloud-based platforms. This is a delivery-focused engineering role, not a QA or orchestration-only position. Key Responsibilities • Design, develop, and maintain enterprise ETL pipelines supporting large-scale data platforms • Build and optimize Python-based data transformation logic (data A → B implemented in Python) • Develop scalable data processing solutions using Spark and Databricks • Support enterprise analytics and regulated reporting initiatives • Implement data validation, reconciliation, and audit-traceable pipelines • Write and optimize complex SQL across enterprise data platforms (Snowflake, Oracle, SQL Server, Teradata) • Participate in legacy ETL modernization initiatives (e.g., Informatica or shell to Python conversions) • Support cloud-based data architectures within Azure environments • Collaborate with architects, analysts, QA, and reporting teams to ensure data quality and accuracy • Participate in CI/CD, code reviews, and source control using Azure DevOps and GitHub • Support production operations, incident resolution, and root-cause analysis Required Qualifications • 5+ years of enterprise data engineering experience • 5+ years of hands-on ETL development (Informatica PowerCenter, Azure Data Factory, or similar tools) • 5+ years of Python development focused on data engineering and transformation logic • 3+ years of Spark-based processing (Databricks or equivalent) • Strong SQL expertise across large relational databases • Experience working in regulated, audit-sensitive environments • Strong analytical, troubleshooting, and problem-solving skills • Bachelor’s degree or higher in Computer Science, Engineering, Analytics, or related field Preferred Qualifications • Experience supporting large enterprise data warehouse environments • Healthcare or public-sector data experience preferred • Experience with data quality frameworks and reconciliation processes • Scripting experience (PowerShell or Bash) • Experience designing or consuming REST APIs • Cloud-based data engineering experience in Azure • Azure data or analytics certifications Work Environment This role is fully remote within the continental U.S. Occasional travel to Springfield, IL may be required based on project needs. Onboarding: This role will require a background check and drug screen.