Enterprise Data Architect 3, Digital Technology Solutions

Job Overview

The Enterprise Data Architect is responsible for defining, governing, and advancing the enterprise data architecture needed to support trusted reporting, analytics, AI, institutional decision-making, operational systems, and digital transformation. This role establishes architectural direction for the university's modern data platform, including data integration patterns, medallion architecture, data modeling standards, metadata and lineage practices, data quality expectations, master/reference data patterns, and secure, scalable data product design. The role explicitly includes architecture across major ERP and administrative systems, including Oracle/PeopleSoft Catalyst SIS, SAP S/4HANA / UC Flex HR-Finance, SAP SuccessFactors Employee Central, Workforce Central/timekeeping integrations, and related reporting and integration dependencies.

The role partners closely with data engineering, analytics, enterprise applications, ERP/SIS/CRM teams, InfoSec, data governance, institutional research, business stakeholders, and technology leadership to ensure data solutions are reliable, reusable, well-documented, secure, and aligned with enterprise strategy. The Enterprise Data Architect provides technical leadership across Snowflake, Informatica, cloud data services, APIs, SaaS platforms, Oracle and SAP data domains, Salesforce CRM, and emerging AI-ready data capabilities.

This is a hybrid position.

Essential Functions

• Define standards for naming, describing, managing, modeling, cleansing, enriching, transforming, moving, storing, searching and delivering all data within the enterprise.
• Serve as liaison between governance and data consumer representatives and data solution development, integration teams. Inform and interpret data project sponsors. Understand how data is, or will be, used and implication on people, processes, products and technology.
• Provide framework, stewardship, governance and decision making for management of data for project development teams, business users and other stakeholders.
• Balance short-term versus long-term actions, strategic versus tactical requirements, while continuing to move forward towards the strategic vision.
• Develop enterprise data management methodology and standards and promote to both technology and business throughout the company.
• Put processes around metadata to ensure an integrated definition of data for enterprise information, and to ensure the accuracy, validity, and reusability of metadata.
• Participate in developing consistent definitions for common reference data and master data management.
• Establish measures to chart progress related to completeness and quality of metadata for enterprise information, to support reduction of data redundancy and fragmentation, elimination of unnecessary movement of data, and improvement of data quality.
• Provide input on large-scale projects and roadmaps for compatibility with the vision.
• Drive selection of data management tools, and the development of standards, usage guidelines and procedures for those tools.
• Define the process to resolve cross-organizational data management issues.
• Strong coordination with other enterprise and application architects from operational systems.
• Perform related duties based on departmental need. This job description can be changed at any time.

Required Education

Bachelor's Degree in Computer Science, Information Technology, Computer Engineering, or related field. Seven (7) years of relevant work experience and/or other specialized training can be used in lieu of education requirement.

Required Experience

Three (3) years of related experience.

Additional Qualifications Considered

• An understanding of Business, Functional and Data modeling across various industries like Enterprise Software, High Tech and others.
• Experience in a higher education environment.
• In depth experience of Enterprise Data Modeling including Enterprise Data Warehouse and Messaging models.
• A practitioner of architecture principles, able to lead an organization through transformation via large scale projects that has impact across master data, transactional data and BI.