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.

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.

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

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data engineeringETLELTdata pipelinesdata modelingdata transformationSQLdata warehousingcloud-based data environmentsdata governance

Soft Skills

project managementanalytical skillsproblem-solvingcommunicationmentorshipcustomer serviceattention to detailadaptabilityteamworkprofessional judgment