Senior Data Engineer – Python ETL (Data Quality, Spark/Databricks)
Design, build, and maintain enterprise ETL pipelines for large-scale data platforms. Develop Python-based data transformation logic and scalable Spark/Databricks solutions. Ensure data quality, compliance, and collaboration across analytics teams.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
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Job Description
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
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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
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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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