Senior Manager, Data Lakehouse
Listed on 2026-05-31
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IT/Tech
Data Engineer, Data Science Manager
Duties and Responsibilities
- Execute and operate approved Data Lakehouse initiatives aligned with UMGC’s enterprise data and analytics strategy, ensuring the Databricks platform is reliable, secure, and scalable to meet business needs.
- Provide technical and people leadership to a team of data engineers and architects, supporting performance management, coaching, skills development, and continuous improvement in alignment with established goals.
- Oversee data architecture and engineering activities, including ELT/ETL and CI/CD pipelines and data integration across Bronze, Silver, and Gold layers to support analytics, reporting, operational, and AI use cases.
- Monitor and maintain day‑to‑day platform operations, including performance, availability, and issue resolution, ensuring service levels and operational expectations are met.
- Implement and maintain data governance, security, quality, and compliance controls in partnership with information security, legal, and compliance teams, ensuring adherence to regulatory and institutional requirements.
- Collaborate with data scientists, analysts, IT, and business stakeholders to deliver approved analytics, AI, and self‑service capabilities within established architectural, security, and governance standards.
- Contribute to the evaluation and adoption of new tools, technologies, and platform enhancements, providing technical recommendations to improve performance, scalability, usability, and cost efficiency.
- Manage delivery commitments and operational priorities, supporting resource planning, vendor coordination, and cost optimization under approved operating plans and AVP Enterprise Data oversight.
Strategic leadership, collaboration, accountability, communication excellence, innovation mindset, change leadership.
Skills- Databricks Lakehouse
- Enterprise data platforms
- Cloud analytics
- Data governance
- Agile/Dev Ops
- Stakeholder management
- Offshore team management experience
- Bachelor’s degree in Information Science and Technology, Library and Information Science, Computer Science, Business Analytics, or a related field.
- 7–9 years of experience supporting or delivering enterprise data and analytics platforms.
- 3+ years of experience leading data engineering or analytics teams.
- Higher education data environments; AI/BI integration.
Databricks strongly preferred.
Benefits Package HighlightsHiring Range: $ - $.
- 22 days of paid vacation, 15 days of sick leave, 3 personal days, and 16 paid holidays (17 during general election years).
- Comprehensive health coverage: medical with vision, dental, and prescription plans for individuals and families.
- Insurance options:
Term Life Insurance, Accidental Death and Dismemberment Insurance, and Long‑Term Disability (LTD) Insurance. - Flexible Spending Accounts for medical and dependent care expenses.
- Retirement plans:
Optional Retirement Program (ORP) or Maryland State Retirement and Pension System (MSRPS);
Supplemental Retirement Plans include 401(k), 403(b), 457(b), and various Roth options. - Tution remission for Regular Exempt Staff; spouses and dependent children eligible after two years of service.
The University of Maryland Global Campus (UMGC) is an equal opportunity employer and complies with all applicable federal and state laws regarding nondiscrimination. UMGC is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, national origin, age, marital status, sex, sexual orientation, gender identity, gender expression, disability, religion, ancestry, political affiliation, or veteran status in employment, educational programs and activities, and admissions.
WorkplaceAccommodations
UMGC is committed to creating and maintaining a welcoming and inclusive working environment for people of all abilities. For information about UMGC’s Reasonable Workplace Accommodation Policy or to request an accommodation, applicants can contact Employee Accommodations via email at employee‑accommodations.
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