Senior Data Engineer

Solventum is a new healthcare company focused on improving lives through innovative solutions. In this role, the Senior Data Engineer will design and optimize data processing pipelines, maintain scalable data solutions, and ensure compliance with healthcare standards.

Responsibilities:

• Data Pipeline Development: Design, build, and optimize robust ETL/ELT processing pipelines to ingest and transform complex healthcare data from disparate sources
• Data Modeling & Architecture: Architect and maintain scalable data solutions utilizing Snowflake as our primary data cloud, leveraging both Azure and AWS environments. Design and deploy efficient star schemas and dimensional models to optimize for analytical querying
• Semantic Layer Development: Build and maintain a robust semantic layer to translate complex data structures into business-friendly metrics, ensuring consistent definitions and seamless integration with downstream reporting tools
• Master Data Management: Collaborate closely with data leadership to synchronize disparate data streams, ensuring data quality and the successful deployment of Customer 360 initiatives
• Healthcare Compliance: Ensure all data architecture, storage, and processing strictly adhere to healthcare compliance standards (e.g., HIPAA, HITRUST) and best practices for handling Protected Health Information (PHI)

Requirements:

• Bachelor's Degree or higher AND at least (8) eight years of proven professional experience as a Data Engineer in a private, public, government or military environment
• Deep understanding of the healthcare landscape, including electronic health records (EHR), healthcare data structures, and strict regulatory compliance requirements (HIPAA)
• Hands-on, advanced proficiency with Snowflake
• Strong working knowledge of cloud computing platforms, specifically Azure and AWS
• Demonstrated expertise in building automated ETL processing workflows
• Proven experience designing dimensional data models (specifically star schema development)
• Experience building and maintaining a semantic layer for enterprise analytics
• Strong analytical skills with the ability to troubleshoot complex data pipeline issues, optimize system performance, and translate business requirements into reliable technical solutions