Data Engineering Team Lead

The University of Maine System is seeking a Data Engineering Team Lead to provide technical and operational leadership for enterprise data engineering, analytics, and data governance services within our Data Systems and Integration Team. This role leads a multidisciplinary team of Data Engineers, Business Intelligence Analysts, and data governance professionals. The Team Lead is accountable for the reliability, quality, and performance of enterprise data pipelines, analytical platforms, and governance workflows that support institutional reporting, decision-making, and compliance. Reporting to the Executive Director of Web and Data Services, this position partners closely with enterprise architecture, information security, privacy, records management, ERP services, campus IT, and administrative leaders to ensure scalable, secure, and standards-aligned data solutions across the University System.

The Data Systems and Integration Team (DSIT) is a part of the University of Maine System's Information Technology Enterprise Services department. The DSIT team supports enterprise data services that enable reporting, analytics, data governance, and secure data movement across core university systems. The group works in close partnership with campus stakeholders, enterprise application teams, and information security to deliver reliable, well-governed data services that support institutional operations and decision-making.

What You'll Do

• Lead and manage daily and long-term operations of the Data Engineering team.
• Oversee enterprise data pipelines, ETL/ELT processes, analytical platforms, and governance workflows.
• Ensure adherence to enterprise data architecture, integration standards, governance practices, and security requirements. 
• Prioritize work across competing institutional demands while balancing service reliability and operational risk.
• Guide the development of scalable data models, semantic layers, and metadata documents.
• Coordinate incident response, data quality remediation, and continuous improvement initiatives.
• Mentor staff in professional development, engineering best practices, and service delivery excellence.
• Collaborate across IT and institutional leadership to support enterprise data initiatives.

Please review the full job description to learn more. 

Schedule: The standard work hours are Monday through Friday, 8:00 AM to 5:00 PM. Occasional evening and weekend work may be required.

Salary: The hiring range for this position is $80,000 to $90,000 (non-negotiable) and is commensurate with training, education, and experience.

Benefits: The University of Maine System offers a highly competitive benefits package that includes (but is not limited to):

• 13 paid holidays plus earned vacation and sick time
• Health, Dental, and Vision insurance
• Short-term disability insurance and employer-paid long-term disability insurance
• Employer-paid basic life insurance and supplemental life insurance
• Tuition waiver program for employees and their dependents (spouse, domestic partner, and dependent children)
• 403(b) retirement plan with employer contribution

To learn more, please review the Benefits Information Summary.

Qualifications

Required:

• Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field AND seven (7) years of relevant experience supporting or managing enterprise data engineering, analytics platforms, or data services in a complex organizational environment.
  • OR a master's degree in a related field AND five (5) years of relevant professional experience supporting or managing enterprise data engineering, analytics platforms, or data services in a complex organizational environment.
• Experience supervising technical staff or serving in a formal Lead Engineering capacity with responsibility for project delivery and mentorship.
• Experience evaluating and overseeing the development and operation of data pipelines and ETL/ELT processes.
• Experience overseeing cloud-based data environments, including evaluating performance, reliability, and cost trends.
• Ability to communicate effectively with technical and non-technical stakeholders, translating complex data concepts into actionable insights.
• Strong project management skills with the ability to manage multiple priorities, m