Data Engineering Team Lead
About The Position
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.
Requirements
- 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, meet deadlines, and adapt to changing requirements.
- Strong analytical and problem-solving abilities with sound professional judgment.
- Ability to document technical process and maintain transparency in development practices.
- Demonstrated commitment to high-quality customer service
- Strong understanding of relational databases, data modeling practices, data transformation concepts, and fundamentals of data warehousing.
- Familiarity with structured and unstructured data, APIs, and modern data architecture concepts.
- Ability to evaluate complex SQL-based data transformations for quality, performance, and accuracy.
- Ability to learn new technologies quickly and apply them effectively.
- Ability to work independently and within a team, managing priorities in a dynamic environment.
- Excellent attention to detail and commitment to high-quality work.
Nice To Haves
- Experience with modern data pipelines or orchestration technologies (e.g., Airflow, cloud-native schedules, containerized workflows).
- Experience with enterprise integration platforms (e.g., Boomi or similar tool).
- Experience with event-streaming or messaging platforms (e.g., Kafka or similar technologies).
- Experience supporting BI tools and analytical semantic modeling, preferably Power BI.
- Experience with cloud data storage, object stores, or hybrid data architecture.
- Experience with Agile development practices, CI/CD pipelines, and automation.
- Experience in environments involving PeopleSoft ERP or similar administrative platforms.
- Experience leading a modernization of legacy data systems to cloud-native platforms.
- Experience managing agile development teams.
- Experience enforcing data standards, data governance practices, or security requirements within operational teams.
Responsibilities
- 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.
Benefits
- 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
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
