Senior Clinical Data Associate Jobs in Vermont (NOW HIRING)

Department

BSD CRI - Administration

About the Department

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.

Job Summary

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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Preferred Qualifications

Job Family

Information Technology

Role Impact

People Manager

Scheduled Weekly Hours

40

Drug Test Required

No

Health Screen Required

No

Motor Vehicle Record Inquiry Required

No

Pay Rate Type

Salary

FLSA Status

Exempt

Pay Range

$120,000.00 - $170,000.00

The included pay rate or range represents the University's good faith estimate of the possible compensation offer for this role at the time of posting.

Benefits Eligible

Yes

The University of Chicago offers a wide range of benefits programs and resources for eligible employees, including health, retirement, and paid time off. Information about the benefit offerings can be found in the Benefits Guidebook.

Posting Statement

The University of Chicago is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender, gender identity, or expression, national or ethnic origin, shared ancestry, age, status as an individual with a disability, military or veteran status, genetic information, or other protected classes under the law. For additional information please see the University's Notice of Nondiscrimination.

Job seekers in need of a reasonable accommodation to complete the application process should call 773-702-5800 or submit a request via Applicant Inquiry Form.

All offers of employment are contingent upon a background check that includes a review of conviction history. A conviction does not automatically preclude University employment. Rather, the University considers conviction information on a case-by-case basis and assesses the nature of the offense, the circumstances surrounding it, the proximity in time of the conviction, and its relevance to the position.

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