PartsSource
Healthcare
SeniorDataEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Data Engineer at PartsSource”
Industry & Context.
Problem solving
How You'll Work.
Team & Collaboration
Analytics; Product; Business stakeholders; Internal engineering standards; Junior data engineers
Full Job Description
PartsSource is the leading technology and software platform for managing mission-critical healthcare equipment. Trusted by over 5,000 US hospitals and 15,000 clinical sites, PartsSource empowers providers and service organizations to maximize clinical availability for patient care and automates the procurement of parts, services and training through a unique digital experience. PartsSource team members are deeply committed to our mission of Ensuring Healthcare is Always On®, which is foundational to our success and growth. Our vibrant culture is built upon aligned values, shared ownership, mutual respect, and a passion for collaborating to solve complex customer problems. About the Job Opportunity The Senior Data Engineer plays a leading role in modernizing our enterprise data platform as we transition from legacy systems (DB2, Talend) to a cloud-native stack built on AWS and Databricks. This is a hands-on individual contributor role responsible for designing and building scalable pipelines, setting best practices, and mentoring peers — while working closely with Analytics, Product, and business stakeholders to deliver reliable, well-governed data across the organization. What You'll Do Design, develop, and optimize ETL/ELT pipelines using SQL, Python, Talend, and Databricks to support analytics, reporting, and operational data needs. Lead and support migration of data systems from DB2/SQL Server to Databricks, including performance benchmarking, validation, and pipeline refactoring. Guide the phased replacement of Talend with Databricks-native processes; assist in evaluating and implementing emerging tools and frameworks. Establish and enforce data quality, observability, and lineage standards — including monitoring and alerting for key pipelines. Design data models and schemas for reporting and analytics use cases, applying normalization and denormalization best practices. Act as a technical thought partner in data architecture discussions, aligning platform decis
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