Job Description

Responsibilities*
Data Architecture & Solution Design

Architect and implement end-to-end data warehousing solutions that integrate diverse systems and enable actionable metrics, reporting, and AI/ML use cases
Design and build scalable, resilient, and maintainable data architectures across cloud platforms
Establish and enforce standards for data modeling, pipeline development, and documentation
Advanced Data Modeling & Engineering

Apply expert-level dimensional modeling techniques (e.g., Kimball methodology, Star and Snowflake schemas) to design robust logical and physical data models
Build and optimize complex ELT workflows and data pipelines across a large number of systems
Lead performance tuning and cost optimization efforts across Snowflake, Matillion, and related cloud technologies
Data Governance, Security & Compliance

Contribute to and help operationalize scalable data governance practices
Ensure compliance with data privacy and security standards (e.g., FERPA, GDPR) within a higher education context
Promote high standards of data quality, documentation, and operational reliability
Strategic Partnership & Technical Leadership

Partner with stakeholders across Engineering, Online Learning, XR, and other teams to translate complex business needs into resilient technical solutions
Mentor and support other data engineers, fostering a culture of rigor, collaboration, and continuous improvement
Evaluate and thoughtfully incorporate emerging technologies, including AI-enabled tools, into engineering workflows
What You'll Do
The Center for Academic Innovation (CAI) at the University of Michigan is seeking a highly qualified Data Engineer Senior to join our growing Data and Business Intelligence team. As we expand our Data, BI, and AI/ML capabilities in support of innovative educational solutions, the Michigan Online platform, and other CAI initiatives, this newly created role will be instrumental in designing, implementing, and optimizing a world-class data infrastructure. You will collaborate closely with cross-functional teams to translate complex business needs into robust data solutions. In addition to hands-on engineering, you will mentor colleagues and contribute to a culture of technical rigor, innovation, and continuous improvement, with ongoing opportunities to further grow and refine your technical leadership skills.

Required Qualifications*
Bachelor's degree required. Degree in Computer Science, Data Engineering, Information Systems, or a related field preferred
5+ years of progressively responsible experience in data engineering, data architecture, or related technical roles
Expert-level knowledge of dimensional modeling (Star and Snowflake schemas) and data warehousing best practices
Deep experience with modern ELT frameworks and cloud data platforms (e.g., Snowflake, Matillion)
Proven ability to design, build and scale complex data pipelines across numerous systems
Strong problem-solving, collaboration and stakeholder engagement skills
Ability to independently lead technical initiatives from design through deployment and manage multiple projects using tools like Asana
Ability to learn and appropriately use new technologies to improve processes, communication, and outcomes, including AI-enabled tools where relevant to the role, consistent with university policy and job responsibilities