Senior Data Engineer

Parts Source 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, Parts Source 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.

Parts Source 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.

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.

• 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 decisions with business growth and governance objectives.
• Contribute to internal engineering standards: version control (Git Hub), CI/CD, infrastructure as code (IaC), and documentation.
• Mentor junior data engineers and serve as a technical resource across the team.

• 5+ years of experience in data engineering, data warehousing, or enterprise ETL/ELT development.
• Advanced SQL and experience with relational databases including SQL Server and DB2.
• Hands‑on experience with Databricks — Lakehouse architecture, Unity Catalog, Delta Lake, S3, and IAM.
• Proficiency in Python for pipeline development, automation, and data processing.
• Strong data modeling, query optimization, and performance tuning skills.
• Experience with Git/Git Hub and collaborative development workflows.

• Experience with Semarchy or similar MDM platforms; knowledge of Kafka or real‑time streaming.
• Proficiency with IaC tooling (Terraform, Open Tofu); AWS or Databricks certification a plus.
• Prior experience in a lead or mentoring role within a data team.

• You own the reliability of what you build — you monitor it, fix it, and document it without being asked. Accountability & Execution, Results Driven

• You understand that clean, reliable data drives every decision  partner across teams with patience and clarity because you know the downstream stakes. Clear & Critical Thinking, Relationship Management

• You pick up new platforms and patterns quickly, stay effective through platform migrations, and apply feedback to keep improving. Learning Agility, Resilience

• You elevate the team through code reviews, shared documentation, and proactive knowledge transfer — not just your individual output. Team Orientation, Alignment & Cohesion

• You ask why when existing patterns create complexity, and you bring improvement proposals with engineering context — not just complaints. Curiosity & Problem Solving, Continuous Improvement

• Competitive compensation package with salary, incentives, company ownership/equity, and comprehensive benefits (401k match, health,…