Clinical Research Data Manager Jobs (NOW HIRING)

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.

Responsibilities

• 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 transparent, service-oriented model.
• Operate within a federal recharge center, including:
• Supporting sustainable cost-recovery models
• Aligning effort with funded work and service agreements
• Partnering on budgeting, forecasting, and reporting
• Collaborate with governance, privacy, security, and compliance teams to ensure responsible data use.
• Contribute to continuous process improvement and service maturity.
• Manages professional staff. Establishes performance goals, allocates resources and assesses policies for direct subordinates.
• Recommends departmental plans to maintain administrative data. Ensures that the data is accessible, easy-to-use, flexible, and suitable for various analytical purposes, including joint analyses across multiple domains and interactions across multiple systems.
• Plans additional data warehouse and reporting environments as needed. Manages relationships with the University's primary software suppliers for end-user data access, query, reporting, and display.
• Performs other related work as needed.

Minimum Qualifications

Education:

Minimum requirements include a college or university degree in related field.

Work Experience:

Minimum requirements include knowledge and skills developed through 7+ years of work experience in a related job discipline.

Certifications:

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Education:

• Master's degree in computer science, informatics, or related field.

Experience:

• Experience supporting AI/ML initiatives or advanced analytics in healthcare or research.
• Familiarity with federal grant-funded research environments (e.g., CTSA, NIH-funded programs).
• Experience operating within a recharge or cost-recovery model.
• Knowledge of cloud platforms, scalable analytics infrastructure, and modern data ecosystems.
• Background working in an academic medical center or large research enterprise.

Certifications:

• Epic Report Builder, Epic Caboodle, or other related Epic certifications a plus.
• RN, DNP, MD, or other clinical licensure a plus.

Technical Skills or Knowledge:

• Knowledge of healthcare data including ICD-9, ICD-10, and CPT.

Preferred Competencies

• High level of problem solving and decision-making skills.
• Expert in SQL, Python, R, and Excel.
• Proficiency in relational databases with experience designing transformations, mappings, and working with reference table.
• Knowledge of graphical databases.
• Ability to translate technical information to non-technical audiences.
• Critical thinking and multi-tasking skills with the ability to manage multiple projects.
• Time management skills.
• Proficiency in creating technical specifications, business cases, and other development-related documentation.
• Ability to working through complex problems.
• Knowledge of hospitals and healthcare (experience in AMCs a plus).
• Knowledge of research processes.
• Intellectual curiosity.