Data Engineering Lead

How to Apply

A cover letter and resume are important submissions for the hiring team to get a sense of your experience. In the cover letter, in two pages or less, please let us know how this role aligns with your career aspirations and skill set. Submit both a cover letter and resume as one file (because of system limitations).

What You'll Do

The Center for Academic Innovation (CAI) at the University of Michigan is seeking a highly qualified Data Engineering Lead. As we expand our Data, BI, and AI/ML capabilities to support innovative educational solutions, the Michigan Online platform and CAI internal operations, you will step into this newly created leadership role to guide our data engineering team. You will play a critical role in building scalable data systems, demonstrating outstanding data stewardship, and promoting collaboration through BI and AI community initiatives. Based in Ann Arbor, Michigan and reporting to CAI's Director of Data and Business Intelligence, you will lead a team charged with building our world-class data infrastructure and working collaboratively with internal teams and across campus aligning the work we do with CAI's mission and long-term vision.

Who We Are

About the Center for Academic Innovation

Through curricular innovation, tools for student success, and educational research and analytics, the University of Michigan Center for Academic Innovation is building the future of education. Our vision is a future in which education connects and empowers learners everywhere to reach their full potential throughout their lives. To realize our vision, we make it our mission to collaborate across campus and around the world to create equitable, lifelong educational opportunities for learners everywhere.

About the Data and Business Intelligence Team

The Data and Business Intelligence Team within the Center for Academic Innovation (CAI) at the University of Michigan drives CAI's data strategy, ensuring that data is used responsibly, ethically, and securely. Our team of data engineers, scientists, and analysts powers internal operations and the Michigan Online platform by leveraging data as our universal language for analytics, insights and decision-making. We strive to democratize access to data while upholding strong standards for governance, security, and privacy. Through collaboration and communities of practice, we share innovations, learn from peers, and help foster a culture of data-informed decision-making across CAI and the broader campus.

For more information, please visit our website: Academic Innovation.

Responsibilities*

Data Architecture and Technical Expertise

• Design and implement end-to-end data warehousing solutions, integrating diverse source systems with target applications to create actionable metrics and insights, ensuring scalability, resilience, and maintainability.
• Leverage expert knowledge of dimensional modeling (e.g., Kimball methodology, Star and Snowflake schemas) to build logical and physical data models that support reporting, analytics, and AI/ML use cases.
• Utilize advanced ELT tools and techniques for efficient data processing, while optimizing cloud-based architectures like Snowflake and Databricks for cost efficiency.
• Work seamlessly with structured and unstructured datasets, managing multiple source and target systems with varying access levels.
• Incorporate AI tools into daily workflows, coaching team members on their use within a structured framework to enhance data engineering and internal operations.

Team Leadership and Strategic Alignment

• Lead and mentor data engineers and architects, providing oversight, performance management, and fostering a culture of shared ownership and excellence in data engineering.
• Align team priorities with organizational and stakeholder goals to ensure cohesive project delivery and contribute to strategic goal-setting within the data domain. Lead discovery sessions with stakeholders, ensuring clear and effective communication with non-technical audiences.
• Facilitate collaboration across teams and domains to achieve shared objectives, while planning for team growth to support long-term data capabilities.
• Guide early career team members, promoting professional development and a standard of excellence across CAI.

Cross-Functional Collaboration & Community Building

• Partner with cross-functional teams in Engineering, Online Learning, and XR to gather requirements, communicate effectively with non-technical stakeholders, and deliver cohesive data solutions.
• Proactively identify opportunities to improve data processes, track key metrics for team objectives, and ensure a service model that supports positive stakeholder engagement.
• Co-host the BI + AI Community of Practice and lead monthly Data Hours to foster collaboration, share insights, and showcase the team's work across the university campus.

Required Qualifications*

• Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related field is a plus.
• 10-12 years of experience and progressive responsibility in data engineering, data architecture, or related technical roles.
• Leadership & People Management: A servant leader with proven ability to lead data teams, including people leadership, hiring, mentoring, and aligning priorities with organizational goals.
• Technical Acumen: Expert-level knowledge of dimensional modeling, Star and Snowflake schemas; expert-level knowledge of latest ELT tools and techniques; deep understanding of cloud-based architectures including Snowflake and Databricks; fluency in building scalable and complex data pipelines between large numbers of source and target systems. Fluency with salesforce.com clouds and familiarity with cloud-based hyperscaler solution optimizations are a huge plus.
• Architectural Skills: Demonstrated experience architecting end-to-end data warehousing solutions, building logical and physical data models, and thinking comprehensively across data and technology ecosystems. Prior experience with Snowflake, Databricks and Matillion are a huge plus.
• Data Governance and Security: Prior experience establishing scalable data governance practices and ensuring compliance with data privacy and security standards (e.g., FERPA, GDPR).
• Stakeholder Engagement: Proven ability to lead discovery sessions and communicate effectively with non-technical stakeholders.
• Project Management & Organizational Skills: Demonstrated capability to independently manage projects from start to finish and handle multiple tasks, including working on projects that involve multiple internal teams and using enterprise technology tools like Asana to streamline collaboration.
• Analytical & Problem-Solving Aptitude: Strong analytical skills and proactive in identifying issues and designing solutions. Ability to build reports and dashboards using Looker and Tableau.
• Communication & Collaboration: Proven ability to build rapport and collaborate effectively with internal teams as well as external stakeholders.
• Industry Interest: Familiarity with trends in data technologies and educational analytics coupled with a proactive, results-oriented mindset and eagerness to learn.

Modes of Work

Positions that are eligible for hybrid or mobile/remote work mode are at the discretion of the hiring department. Work agreements are reviewed annually at a minimum and are subject to change at any time, and for any reason, throughout the course of employment. Learn more about the work modes.

Additional Information

The mode of work for this position is Hybrid with a minimum of 4 days in the office per week, Monday through Thursday, with an option of remote work on Fridays. On occasion, you may be required and must be available to work onsite on Fridays if necessitated by our center's policy and domain leadership or by your job requirements.

Must have legal authorization to work in the United States.

The salary for this position will be based upon the selected candidate's education and experience.

Excellent benefits are available, for details, see http://benefits.umich.edu/

Salary Information

The general salary range for this position is $100,000 - $120,000. Candidates can expect to be paid a competitive and equitable salary. Factors used to determine salary include education level, experience, knowledge and skills for the position and salaries that are currently established within the unit. All candidates are encouraged to discuss salary questions to honor alignment and transparency throughout the recruiting process.

Organizational Statement on Harassment

We believe all individuals deserve to be treated with respect and dignity and have the right to work in a professional atmosphere that promotes mutual respect and a safe space for collaboration. Any concerns shared with Individuals with Reporting Obligations in the Center for Academic Innovation will be reported to the Equity, Civil Rights, & Title IX Office to be reviewed and addressed, and the Center for Academic Innovation encourages reporting of any forms of harassment including sexual and gender-based harassment.

Background Screening

The University of Michigan conducts background checks on all job candidates upon acceptance of a contingent offer and may use a third party administrator to conduct background checks.
Background checks will be performed in compliance with the Fair Credit Reporting Act.

Application Deadline

Job openings are posted for a minimum of seven calendar days. This job may be removed from posting boards and filled anytime after the minimum posting period has ended.

Decision Making Process

Applications will be reviewed as received throughout the posting period and continue until the position is filled.

U-M EEO Statement

The University of Michigan is an equal employment opportunity employer.

268464

Data Engineering Lead

Data Engineer Lead

Ann Arbor Campus

Hybrid

Full-Time

Regular

Exempt

Vp Acad Innovation

Center for Academic Innovation

9/10/2025 - 10/10/2025

$100,000.00 - $120,000.00

Information Technology