Manager, Clinical Data Engineering

Department Overview

The mission of the Information Technology Group (ITG) is to provide and support technology and information services that enable OHSU to be a national leader in health and science innovation. The work of the Business Intelligence and Advanced Analytics (BIAA) Division ensures that the informational assets of the OHSU enterprise are leveraged to enhance financial, clinical, operational, and research decision-making.

 

Reporting to the Director of Clinical Data and Analytics, this leadership position is responsible for leading the design, development, and technical stewardship of data engineering systems that enable efficient, reliable, and scalable data processing and analysis across OHSU Health. The principal duty of this position is leading a team of Data Engineers responsible for developing, documenting, and optimizing data pipelines, data integration processes, and data transformations that support enterprise reporting, analytics, and downstream applications.

Function/Duties of Position

Data Engineering Team Leadership & Talent Development

Provides direct leadership, accountability, and professional development for the Clinical Data Engineering team to ensure high-quality, sustainable delivery of enterprise data assets.

• Leads recruitment, onboarding, retention, and performance management in alignment with OHSU’s standards.
• Conducts regular 1:1 meetings and GROW conversations to establish clear goals, foster growth, and address performance needs.
• Holds staff accountable for deliverables, quality standards, documentation, and timelines.
• Schedules and conducts regular team meetings to communicate project goals, divisional priorities, and relevant ITG and OHSU updates.
• Builds senior engineering capability and distributed technical leadership across the team.
• Use working experience of industry best practices to reinforce engineering standards, including testing discipline, documentation rigor, and sustainable design practices.
• Leads staff in expanding skills, modernizing BI processes, improving SDLC discipline, and advancing data warehousing capabilities in support of OHSU’s BI strategy.
• Ensures engineers operate at the top of their license by clarifying roles, reducing unnecessary managerial intervention, and promoting autonomy within defined standards.

Data Pipeline Design, Development & Quality Oversight

Provides oversight and direction for the design, development, validation, and ongoing accuracy of scalable, secure, and well-governed data pipelines.

• Ensures standard system development methodologies are followed for data flows, transformations, and warehouse structures.
• Implements structured quality assurance processes and peer review to ensure code quality.
• Develops defect tracking and resolution workflows that promote accountability, root-cause analysis, and prevention of recurring issues.
• Oversee the maintenance of version-controlled change logs and promotion histories for all production data assets.
• Ensures complete and accurate metadata documentation for data models, transformations, lineage, and business logic to support transparency and downstream trust.
• Establishes monitoring and validation mechanisms to detect data defects and unexpected drift.
• Promotes reuse of canonical data structures and alignment with enterprise data models to prevent duplication and fragmentation.
• Escalates complex technical issues to architects or subject matter experts when appropriate and ensures resolution plans are developed and executed.
• Ensures engineering practices align with OHSU data governance standards and security directives.
• Leads the planning and phased transition of data engineering workloads toward modern cloud-based platforms that support the use of advanced analytics, machine learning, and AI capabilities.

Partnerships and Service Delivery

Serves as the primary data engineering liaison to clinical and operational partners, providing well-defined engineering initiatives and managing expectations regarding scope, sequencing, and tradeoffs.

• Acts as a service partner, ensuring responsive and reliable engineering support for operational and enhancement requests.
• Partners with CLBI leaders and business partners to refine and prioritize initiatives aligned with organizational goals.
• Establishes and governs structured intake and backlog management processes, ensuring work meets defined readiness criteria prior to development.
• Communicates engineering capacity, constraints, risks, and sequencing tradeoffs transparently and consistently.
• Facilitates structured discovery and planning sessions for data engineering initiatives to clari