Manager of Clinical Research Data Warehousing

Department

BSD CRI - Administration

The Center for Research Informatics (CRI) is an organization within the Biological Sciences Division (BSD) that provides informatics resources and services to BSD faculty. Five main services comprise the CRI's operations: applications development, bioinformatics, scientific computing, data science and AI, and clinical research data warehousing. Through these service lines, the CRI enables research of the highest scientific merit and advances the state of the art of clinical and translational informatics.

The CRI recruits exceptional candidates looking to leverage state-of-the-art technologies to deliver innovative and exciting solutions to biomedical researchers.

The Manager of Clinical Research Data Warehousing provides strategic, managerial, and technical design leadership for the institution's clinical research data warehouse and related analytic assets. Operating within a matrixed academic medical center environment, this role partners closely with senior academic and hospital leadership, faculty investigators, and multidisciplinary technical teams to ensure clinical data are transformed into trusted, interoperable, and AI-ready research assets.

This role is intentionally designed as a hybrid management position: the Manager is accountable for strategy, architecture, prioritization, team leadership, and optimization of technical solutions, while generally guiding and overseeing implementation rather than serving as the primary individual contributor. The Manager plays a critical role in enabling faculty-funded research, supporting grant-driven deliverables, and ensuring sustainability within a federal recharge center framework.

• Strategic Leadership & Institutional Alignment
• Under the direction of CRI leadership, define and execute the strategic roadmap for the clinical research data warehouse, with explicit focus on:
• AI/ML-ready data architectures
• Scalable analytics and research enablement
• Interoperability and common data models
• Collaborate with senior academic and hospital leadership to align data warehousing priorities with institutional research, clinical, and translational goals.
• Serve as a trusted partner to faculty leadership and mentors, advising on data feasibility, analytic approaches, and emerging capabilities.
• In coordination with CRI leadership and the technical manager of data warehousing, represent the data warehousing function in enterprise-level discussions related to informatics strategy, data harmonization, and AI readiness.
• Matrixed & Cross-Functional Collaboration
• Operate effectively in a matrixed environment, coordinating across reporting lines, service teams, and governance bodies.
• Collaborate closely with:
• Application development teams to align data pipelines, APIs, and research platforms
• HPC and scientific computing experts to support large-scale analytics and AI/ML workflows
• Bioinformatics and data science teams to integrate clinical data with multi-modal research datasets
• Faculty investigators and research teams to translate funded research aims into data and analytic solutions
• Act as a connector and translator between technical teams, researchers, and leadership.
• Data Architecture, Modeling & Interoperability
• Provide architectural oversight for the design and optimization of clinical research data assets.
• Lead adoption and governance of common data models (e.g., OMOP, PCORnet, or equivalent) and ensure analytic fitness for research and AI use cases.
• Advance interoperability strategies leveraging standards such as FHIR, modern APIs, and modular data services.
• Ensure documentation, data provenance, and metadata practices support reproducibility, reuse, and responsible AI development.
• ETL Oversight & Technical Design Optimization
• Oversee (but do not primarily perform) the development and optimization of ETL pipelines ingesting data from Epic EMR systems (e.g., Clarity, Caboodle, Cosmos) and other sources.
• Set technical standards, review designs, and guide implementation decisions to ensure performance, reliability, and scalability.
• Partner with engineers to modernize pipelines using automation, cloud-native patterns, and best practices in data engineering.
• Ensure strong data quality, validation, and refresh processes aligned with funded research commitments.
• Research Enablement & Faculty Support
• Directly support faculty-funded research, ensuring data assets meet grant timelines, deliverables, and compliance requirements.
• Advise investigators and project teams on cohort discovery, longitudinal analysis, and real-world data use.
• Enable AI- and ML-driven research by ensuring datasets are analytically valid, well-structured, and performance-optimized.
• Balance self-service data access with appropriate governance and stewardship.
• Management, Operations & Recharge Center Responsibilities
• Lead, mentor, and develop a team of data engineers, analysts, and related staff.
• Prioritize work across competing research and institutional demands in a…