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

Senior Data Engineer – Python ETL (Data Quality, Spark/Databricks) Remote - US Based Overview 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. {"@context":"http://schema.org","@type":"JobPosting","baseSalary":null,"datePosted":"2026-06-22","validThrough":"2027-06-22","description":"Senior Data Engineer – Python ETL (Data Quality, Spark/Databricks)

Remote - US Based

OverviewWe 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.

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