MSR Technology GroupRemote
Senior Data Engineer – Python ETL (Data Quality, Spark/Databricks)
United States of America
Contract
2 hours ago
No H1B
Key skills
PythonETL developmentSparkDatabricksSQLInformatica PowerCenterAzure Data FactoryEnterprise data engineeringRegulated/audit-sensitive environment experienceData quality frameworksReconciliation processesAzure cloudAnalytical skillsTroubleshootingShellBashPowerShellETLData EngineeringAnalyticsSnowflakeAzureAzure DevOpsOracleSQL ServerGitHubSource ControlCI/CD
About this role
MSR Technology Group is seeking a hands-on Senior Data Engineer 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.
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
Requirements:
- 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
- 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