Lead Data Architect

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.

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.
• 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 across student, employee, alumni, and affiliate records.
• Builds data quality checks, lineage, and auditability into pipelines by design.
• 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 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.
• Coordinates architecture-affecting changes through IT Services change management.
• Mentors data engineers and developers, raises engineering practice across the team, and grows architecture skills.
• Leads the development of Business Intelligence (BI) and other analytical applications.
• Provides expertise in planning, testing, and roll-out of patches and upgrades to the BI and analytic software.

Minimum Qualifications

Education: Minimum requirements include a college or university degree in related field. Work Experience: Minimum requirements include knowledge and skills developed through 7+ years of work experience in a related job discipline.

Preferred Qualifications

• Bachelor's degree in computer science, information systems, data science, or a related field. Master's degree a plus.
• A track record of leading data architecture, setting the standards, patterns, and roadmap that other engineers build to.
• Designing and leading enterprise data architecture in a complex organization, ideally higher education or another federated environment.
• Hands-on experience with data warehouse and data integration platforms such as Oracle databases, Oracle Data Integrator, and Hadoop-based platforms.
• Modern cloud data platforms and lakehouse patterns, including migrating workloads from an on-premises estate.
• Governing cloud data platforms: workspace design, capacity planning, access models, and cost management.
• Data modeling for analytics: relational, dimensional, and semantic layers.
• Metadata management, data catalogs, and data quality frameworks.
• Integrating data from enterprise systems such as ERP, human capital, student information, and CRM platforms.
• Enabling AI on enterprise data: semantic layers, governed access patterns, and emerging standards such as the Model Context Protocol.
• Systems thinking, seeing the whole estate and how a change in one place lands in another.
• Clear communicator who explains architecture to non-technical leaders and writes it down.
• Leads through partnership and influence across teams that own the hosting, access, and source systems.
• Sound judgment on build, buy, and retire, with cost and risk in view.
• Coaches others and builds capability across the team.
• Comfortable with ambiguity and a changing environment.

Working Conditions

Hybrid work schedule, onsite and remote as determined by business needs.