Manager, Clinical Data Engineering at Oregon Health & Science University – Portland, Oregon

Manager, Clinical Data Engineering

US--Remote

Requisition ID: 2026-38484
Position Category: Management/Supervisory
Job Type: Unclassified Administrative
Position Type: Regular Full-Time
Posting Department: Information Technology Group (ITG)
Posting Salary Range: $103,334 - $175,614 per year, with offer based on experience, education and internal equity
Posting FTE: 1.00
Posting Schedule: Typically Monday - Friday
Posting Hours: Business Hours, typically 8:00am - 5:00pm PT
HR Mission: Central Services
Drug Testable: No
LinkedIn Job Code: LI-LP1

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 clarify business objectives, technical implications, scope, and sequencing.
• Leads engineering initiatives requiring structured planning, including development of timelines, milestones, dependencies, and resource allocation to ensure successful delivery.
• Monitors initiative progress, mitigates risks, and drives work to completion while maintaining alignment with partner expectations.
• Communicate initiative status and escalate conflicts in priority or resource allocation appropriately while maintaining alignment across partner groups.
• Determines and prioritizes required engineering work related to upgrades, technical dependencies, regulatory changes, and system maintenance activities.

Continued professional development and other duties as assigned.

Required Qualifications

• Bachelor's degree in computer science or related field and six years or work experience in the information and technology field; OR
• Advanced degree (master's or above) would substitute for four years of work-related experience in the information technology field.

Experience

• Minimum 6 years of progressively responsible experience in data engineering, data warehousing, or business intelligence environments.

• Minimum 2 years leading complex technical projects or people; including planning, execution, risk mitigation, and successful on-time delivery.

• Demonstrated experience implementing structured peer review, testing, QA, and defect management processes in a data engineering or BI environment.

• Experience establishing and maintaining metadata documentation, lineage tracking, and version-controlled change logs for production data assets.

• Demonstrated experience working within formal Systems Development Life Cycle (SDLC) frameworks, including structured promotion controls and release management.

• Experience facilitating structured meetings to gather requirements, define scope, and manage expectations.

• Experience developing and maintaining technical documentation for data models, ETL processes, and reporting assets.

Knowledge, Skills, and Abilities

• Strong understanding of data warehouse and data lake architectures, including dimensional and relational modeling principles.

• Experience establishing and enforcing engineering development standards, code review practices, testing frameworks, and promotion controls.

• Experience implementing data integration and orchestration solutions using tools such as

• Azure Data Factory, Databricks, AWS Glue, or similar services.

• Experience using Azure DevOps or comparable DevOps platforms for source control, CI/CD pipelines, and release management.

• Working knowledge of cloud storage and compute services (e.g., Azure Data Lake, Azure SQL, S3, Redshift, Snowflake, or equivalent).

• Advanced proficiency in SQL for data transformation, profiling, optimization, and validation.

• OHSU’s New Manager Leadership Essentials completed withing the first year of employment

Preferred Qualifications

• Minimum 8 years of progressively responsible experience in data engineering, data warehousing, or business intelligence environments.

• Minimum 4 years leading large, complex technical initiatives or projects, including planning, execution, risk mitigation, and successful on-time delivery.

• Minimum 2 years of direct people management experience, including performance management, staff development, and accountability for delivery outcomes.

• Experience leading projects in cloud-based analytics environments.

• Demonstrated ability to design, develop, and deploy scalable data engineering solutions supporting enterprise analytics environments.

• Proficiency in programming languages such as Python and/or R for data processing, automation, or analytical workflows.

• Experience developing and optimizing ETL/ELT pipelines for reliability, scalability, and performance.

• Ability to monitor, troubleshoot, and remediate issues within data pipelines, data warehouses, and workflow orchestration systems.

• Experience developing and deploying cloud-based data engineering solutions using platforms such as Microsoft Azure, Amazon Web Services (AWS), or comparable cloud environments.

• Understanding of hybrid data architectures and strategies for transitioning on-premise workloads to cloud-based platforms.

• Familiarity with cloud cost optimization, performance tuning, and scalability considerations.

• Fabric Analytics Engineer Associate.

• PMP project management certification.

• Epic Cogito Certifications: Cogito, Clarity Data Model, or Caboodle Developer.

Additional Details

This is typically a Monday - Friday, 8:00am - 5:00pm shift. However, some off hours work may be required to support downtimes, system upgrades and meetings with users.

Work Location is fully remote.

Benefits

• Healthcare for full-time employees covered 100% and 88% for dependents.

• $50K of term life insurance provided at no cost to the employee.

• Two separate above market pension plans to choose from.

• Paid time off - 208 hours per year, prorated for part-time.

• Extended illness bank - 64 hours per year, prorated for part-time.

• 9 paid holidays per year.

• Substantial Tri-Met and C-Tran discounts.

• Employee Assistance Program.

• Childcare service discounts.

• Tuition reimbursement.

• Employee discounts to local and major businesses.