Lead Data Architect

University of Chicago•Chicago, IL

1d•Hybrid

About The Position

The Lead Data Architect sets the architecture for how the University’s administrative data is sourced, modeled, integrated, governed, and delivered, from the current warehouse estate to a modern platform ready for analytics and AI. The role owns the target architecture, standards and patterns, and the roadmap to achieve them, and leads technical design for the team’s highest-impact work. The position partners with infrastructure, information security, privacy, and enterprise application colleagues who own the hosting, access, and source systems on which the architecture depends. During the transition to the target operating model, the Lead Data Architect also owns the health, upgrade, and support roadmap for current data platforms, working with colleagues who administer them day to day. The role leads BI and analytical application development, helps create an integrated reporting and analysis environment, and provides expertise in planning, testing, and rolling out software patches and upgrades. It mentors team members, raises engineering practices, communicates architecture decisions to leaders and partner units, and performs other related work as needed.

Requirements

College or university degree in a related field.
At least 7 years of work experience in a related job discipline, with knowledge and skills developed through that experience.

Nice To Haves

Bachelor’s degree in computer science, information systems, data science, or a related field; a master’s degree is a plus.
Track record of leading data architecture by setting standards, patterns, and roadmaps for other engineers to build to.
Experience designing and leading enterprise data architecture in a complex organization, ideally higher education or another federated environment.
Hands-on experience with data warehouse and integration platforms such as Oracle databases, Oracle Data Integrator, and Hadoop-based platforms.
Experience with modern cloud data platforms and lakehouse patterns, including migration from an on-premises estate.
Experience governing cloud data platforms, including workspace design, capacity planning, access models, and cost management.
Experience in analytics data modeling, including relational, dimensional, and semantic layers.
Experience with metadata management, data catalogs, and data quality frameworks.
Experience integrating enterprise systems such as ERP, human capital, student information, and CRM platforms.
Experience enabling AI on enterprise data through semantic layers, governed access patterns, and emerging standards such as the Model Context Protocol.
Systems thinking and ability to understand how changes across the data estate affect one another.
Clear communication skills, including explaining architecture to non-technical leaders and documenting decisions.
Ability to lead through partnership and influence across teams responsible for hosting, access, and source systems.
Sound judgment about whether to build, buy, or retire, with cost and risk in view.
Ability to coach others and build team capability.
Comfort with ambiguity and a changing environment.

Responsibilities

Define and maintain current-state and target-state architecture for University administrative data, including the multi-year roadmap between them.
Set architecture standards, reference patterns, and design principles for data modeling, integration, pipelines, and data products; review designs against them.
Lead platform modernization options with the team and IT Services partners, developing the technical case, cost, risk, and sequencing for each.
Lead proofs of concept to test platform and architecture options before commitment.
Design for AI readiness, including governed metadata, a shared semantic layer, and clear data contracts.
Lead enterprise data model design across logical, physical, and dimensional models, and design integration architecture across source systems.
Own technical architecture for identity master data so a person resolves consistently across student, employee, alumni, and affiliate records.
Build data quality checks, lineage, and auditability into pipelines by design.
Design classification, access, and privacy controls into the architecture in partnership with Information Security and the Privacy Office.
Support the data governance program through the technical aspects of definitions, the data catalog, and stewardship tooling.
Serve as technical lead on high-priority initiatives, working with data engineers, BI developers, and analytics and AI engineers.
Partner with the Chief Technology Officer’s infrastructure teams on hosting, operations, and capacity, and with enterprise application teams on source-system integration.
Explain architecture choices to leaders and partner units in plain language and document the supporting decision records.
Own the upgrade, version currency, and vendor-support roadmap for current data warehouse, data integration, big data, and cloud data platforms; set direction and priorities, coordinate with day-to-day administrators, and provide hands-on support as needed during the transition.
Coordinate architecture-affecting changes through IT Services change management.
Mentor data engineers and developers, improve engineering practices across the team, and build architecture skills across the team.
Lead development of Business Intelligence (BI) and other analytical applications.
Work toward an integrated reporting and analysis environment that effectively leverages analytical systems and tools.
Provide expertise in planning, testing, and rolling out patches and upgrades to BI and analytic software.
Solve complex problems in developing and interpreting BI and analytics system standards and procedures.
Perform other related work as needed.