Full-Time

Manager of Clinical Research Data Warehousing

Deadline 10/2/26
University of Chicago

University of Chicago

Private research university in Chicago, IL

Compensation Overview

$120k - $170k/yr

Chicago, IL, USA

Hybrid

Hybrid work is required.

Bachelor's, Master's

Category
Data & Analytics (2)
,
Required Skills
Python
High Performance Computing (HPC)
Data Science
R
Epic (EHR)
Graph Databases
SQL
Machine Learning
RDBMS
ETL
Data Engineering
REST APIs
Data Analysis
Excel/Numbers/Sheets

Get referred to University of Chicago

See people who can refer or advise you

Requirements
  • A college or university degree in a related field.
  • At least 7 years of work experience in a related job discipline.
Responsibilities
  • Define and execute the strategic roadmap for the clinical research data warehouse, focusing 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.
  • Advise faculty leadership and mentors on data feasibility, analytic approaches, and emerging capabilities.
  • Represent the data warehousing function in enterprise-level discussions related to informatics strategy, data harmonization, and AI readiness.
  • Coordinate across reporting lines, service teams, and governance bodies in a matrixed environment.
  • Collaborate with application development teams to align data pipelines, APIs, and research platforms.
  • Collaborate with high-performance computing and scientific computing experts to support large-scale analytics and AI/ML workflows.
  • Collaborate with bioinformatics and data science teams to integrate clinical data with multimodal research datasets.
  • Translate funded research aims into data and analytic solutions with faculty investigators and research teams.
  • Provide architectural oversight for the design and optimization of clinical research data assets.
  • Lead adoption and governance of common data models such as OMOP and PCORnet, and ensure analytic fitness for research and AI use cases.
  • Advance interoperability strategies using standards such as FHIR, modern APIs, and modular data services.
  • Ensure documentation, data provenance, and metadata practices support reproducibility, reuse, and responsible AI development.
  • Oversee the development and optimization of ETL pipelines ingesting data from Epic EMR systems, including Clarity, Caboodle, and 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 data-engineering best practices.
  • Ensure data quality, validation, and refresh processes align with funded research commitments.
  • Support faculty-funded research by 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.
  • 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.
  • Support sustainable cost-recovery models within a federal recharge center.
  • Align effort with funded work and service agreements.
  • Partner 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.
  • Manage professional staff, establish performance goals, allocate resources, and assess policies for direct subordinates.
  • Recommend departmental plans to maintain administrative data and ensure it is accessible, easy to use, flexible, and suitable for analytical purposes across multiple domains and systems.
  • Plan additional data warehouse and reporting environments as needed.
  • Manage relationships with the University's primary software suppliers for end-user data access, querying, reporting, and display.
  • Perform other related work as needed.
Desired Qualifications
  • A Master’s degree in computer science, informatics, or a related field.
  • Experience supporting AI/ML initiatives or advanced analytics in healthcare or research.
  • Familiarity with federal grant-funded research environments, such as CTSA or 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.
  • Epic Report Builder, Epic Caboodle, or other related Epic certifications.
  • RN, DNP, MD, or other clinical licensure.
  • Knowledge of healthcare data including ICD-9, ICD-10, and CPT.
  • High-level problem-solving and decision-making skills.
  • Expertise in SQL, Python, R, and Excel.
  • Proficiency in relational databases, including designing transformations, mappings, and working with reference tables.
  • Knowledge of graphical databases.
  • Ability to translate technical information to non-technical audiences.
  • Critical thinking and multitasking 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 work through complex problems.
  • Knowledge of hospitals and healthcare, with experience in academic medical centers as a plus.
  • Knowledge of research processes.
University of Chicago

University of Chicago

View

The University of Chicago is a private research university founded in 1890 in Chicago's Hyde Park neighborhood. It comprises the College, graduate divisions, and professional schools across a broad range of disciplines.

Company Size

N/A

Company Stage

N/A

Total Funding

N/A

Headquarters

N/A

Founded

N/A

Get referred to University of Chicago

See people who can refer or advise you