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.
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.
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.
Continued professional development and other duties as assigned.
Required Qualifications: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.
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.
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.

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