Lead Data Architect

Department OPS ITS - Analytics Intelligence Solutions About the Department IT Services (ITS) collaborates with campus partners to support the mission of the University of Chicago through the consistent delivery of high-quality solutions and services. We provide secure, stable, and reliable infrastructure and applications that support the mission of the University. ITS supports and enables faculty research and teaching with the effective use of technology, simplifies the technology experience for all users, identifies, manages, and mitigates technology risks for the University.

Job Summary The Lead Data Architect sets the architecture for how the University’s administrative data is sourced, modeled, integrated, governed, and delivered, from today’s warehouse estate to a modern platform ready for analytics and AI. This role owns the target architecture, the standards and patterns the team builds to, and the roadmap that moves us there; and it leads the technical design of the team’s highest-impact work.

It partners closely with infrastructure, information security, privacy, and enterprise application colleagues, who own the hosting, access, and source systems the architecture depends on. While the team moves to its target operating model, the role also owns the health, upgrade, and support roadmap for the current data platforms, working with the colleagues who administer them day to day.

Responsibilities Defines and maintains the current-state and target-state data architecture for University administrative data, and the multi-year roadmap between them. Sets architecture standards and reference patterns; designs principles for data modeling, integration, pipelines, and data products, and reviews designs against them. Leads platform modernization options with the team and IT Services partners, building the technical case, cost, risk, and sequencing for each.

Leads proofs of concept to test platform and architecture options before the team commits. Designs for AI readiness, including governed metadata, a shared semantic layer, and clear data contracts, so analytics and AI tools reach governed data safely. Leads the design of enterprise data models, logical, physical, and dimensional, and the integration architecture across source systems. Owns the technical architecture for master data for identity, so one person resolves consistently across student, employee, alumni, and affiliate records.

Builds data quality checks, lineage, and auditability into pipelines by design rather than adding them afterward. Designs classification, access, and privacy controls into the architecture, in partnership with Information Security and the Privacy Office. Supports the data governance program with the technical side of definitions, the data catalog, and stewardship tooling. Serves as technical lead on the team’s highest-priority initiatives, working with data engineers, BI developers, and analytics and AI engineers.

Partners with the Chief Technology Officer’s infrastructure teams on hosting, operations, and capacity, and with enterprise application teams on source-system integration. Explains architecture choices in plain language to leaders and partner units, and writes the decision records behind them. Owns the roadmap for upgrades, version currency, and vendor support of the current data warehouse, data integration, big data, and cloud data platforms, setting direction and priorities while the colleagues and partners who administer them handle day-to-day operations, and steps in hands-on when the team needs it during the transition.

Coordinates architecture-affecting changes through IT Services change management. Mentors data engineers and developers, raises engineering practice across the team, and…