Job description
If you’re passionate about building a better future for individuals, communities, and our country—and you’re committed to working hard to play your part in building that future—consider WGU as the next step in your career.
Driven by a mission to expand access to higher education through online, competency-based degree programs, WGU is also committed to being a great place to work for a diverse workforce of student-focused professionals. The university has pioneered a new way to learn in the 21st century, one that has received praise from academic, industry, government, and media leaders. Whatever your role, working for WGU gives you a part to play in helping students graduate, creating a better tomorrow for themselves and their families.
What You’ll Do
Define and evolve WGU’s enterprise data architecture, including data models, data flows, and platform standards
Establish and maintain data governance frameworks, reference architectures, and enterprise data standards
Align data strategy with institutional priorities, analytics initiatives, and student outcomes
Architect and guide modern data platforms such as data lakes, lakehouses, and data warehouses
Design scalable batch and real-time data pipelines with strong data quality, lineage, and observability
Lead API-first data integration strategies that enable secure, interoperable, and domain-oriented data access
Partner across product, engineering, analytics, and governance teams to influence enterprise data investments
What You’ll Bring
7+ years of experience in data architecture, software engineering, enterprise architecture, or related roles
3 years of experience as an Enterprise Architect or 7 years in a technical leadership role (technical lead, principal engineer, etc.)
Proven success designing and delivering enterprise-scale, distributed systems and technology transformations
Deep expertise in data architecture, including data lakes, warehouses, and lakehouse patterns
Strong background in data modeling across conceptual, logical, and physical layers
Experience with data integration approaches including ETL/ELT, streaming, and APIs
Hands-on experience supporting or enabling AI-driven solutions
Bonus Points
Experience enabling AI and ML workloads, including MLOps or feature stores
Familiarity with modern data stack tools such as Snowflake, Databricks, dbt, or Kafka
Relevant certifications such as TOGAF or AWS or Azure Architect
What to Expect
At WGU, our mission drives everything we do, including how we hire. Our interview experience is designed to give qualified candidates the opportunity to show their best work through meaningful conversations and collaboration.
We thoughtfully review every application and invite forward the candidates whose experience and potential best align with the role and our mission.
Interview Steps
Introductory call
Hiring manager interview
Technical team interview
Work Location
This is a full-time, hybrid role based in our Salt Lake City, Utah office.
Visa Sponsorship
While we welcome applicants from all backgrounds, WGU is not able to provide visa sponsorship for this role.
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Additional Information
- Disclaimer: The job posting highlights the most critical responsibilities and requirements of the job. It’s not all-inclusive.
- Accommodations: Applicants with disabilities who require assistance or accommodation during the application or interview process should contact our Talent Acquisition team at recruiting@wgu.edu.
- Equal Employment Opportunity: All qualified applicants will receive consideration for employment without regard to any protected characteristic as required by law.