layiq

/la·yiq/adjective

worthy; deserving; fitting; suitable.

A role, opportunity, or path that merits attention, time, and pursuit.

Manager of Clinical Research Data Warehousing at University of Chicago | LAYIQ

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.

Manager of Clinical Research Data Warehousing

Employer job description

About the Department

Responsibilities

Minimum Qualifications

Preferred Qualifications

Salary

Benefits Eligible

About this listing