Lead Data Architect

University of Chicago•Chicago, IL

7d•$150,000 - $156,600•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 data warehouse estate to a modern platform prepared for analytics and AI. The role owns the target architecture, architecture standards and patterns, and the roadmap for reaching the target state, while leading the technical design of the team’s highest-impact work. It works closely with infrastructure, information security, privacy, and enterprise application colleagues, who own the hosting, access, and source systems the architecture depends on. During the transition to the target operating model, the role also owns the health, upgrade, and support roadmap for current data platforms, working with the colleagues who administer them day to day. The role defines enterprise data architecture and models, integration patterns, data governance and quality capabilities, and the technical architecture for identity master data. It supports platform modernization and AI readiness, and leads BI and analytical application development. The position mentors engineers and developers, partners across IT Services and University units, and communicates architecture decisions to technical and non-technical audiences. This is an individual-contributor role in the Information Technology job family. The schedule is hybrid, onsite and remote as determined by business needs, with 37.5 scheduled weekly hours. The position is salary, exempt, and benefits eligible. The stated pay range is $150,000.00–$156,600.00.

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.
Master’s degree.
A 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 in 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.
Knowledge of 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 an ability to understand the whole estate and the effects of changes across it.
Clear communication skills, including explaining architecture to non-technical leaders and documenting decisions.
Ability to lead through partnership and influence across teams that own hosting, access, and source systems.
Sound judgment on build, buy, and retire decisions, 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 data architecture for University administrative data, along with 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, costs, risks, and sequencing.
Lead proofs of concept to test platform and architecture options before the team commits.
Design for AI readiness, including governed metadata, a shared semantic layer, and clear data contracts.
Lead the design of logical, physical, and dimensional enterprise data models and source-system integration architecture.
Own the technical architecture for identity master data so individuals resolve 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 technical definitions, the data catalog, and stewardship tooling.
Serve as technical lead on the team’s highest-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 decision records behind them.
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, work with platform administrators, and provide hands-on support when needed during the transition.
Coordinate architecture-affecting changes through IT Services change management.
Mentor data engineers and developers, improve engineering practice across the team, and build architecture skills throughout the team.
Lead the development of Business Intelligence (BI) and other analytical applications, working 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 analytics software.
Solve complex problems in the development and interpretation of BI and analytics system standards and procedures.
Perform other related work as needed.