Senior Analytics Engineer

Analytics

Exempt Regular 3.4

Location: Adelphi, MD

The Senior Analytics Engineer owns the analytics-ready layers of the University's Databricks Lakehouse, transforming curated data into business-ready models and establishing the semantic layer that defines authoritative institutional metrics. This role sets the modeling standards the analytics team builds against, partners directly with business stakeholders to define and govern metrics, and leads the data work behind traditional reporting, AI-powered analytics, and natural language query capabilities. Advanced SQL and Python proficiency are required.

Duties and Responsibilities

• Architect, build, and maintain Gold and Platinum layer data models in Databricks, establishing the design patterns, grain, and business logic the team builds against, and optimizing transformations for performance and cost.
• Own and govern the semantic layer using Databricks metric views, establishing authoritative institutional metric definitions in partnership with business stakeholders and managing version control and downstream impact as those definitions change.
• Lead the curation of datasets, metric views, metadata, instructions, and certified SQL examples that support Databricks AI Genie Agents and AI/BI dashboards; evaluate agent accuracy and drive improvements through model and semantic changes.
• Establish and administer data quality, validation, and reconciliation practices against systems of record; resolve discrepancies to root cause; and define governance, lineage, and access standards through Unity Catalog.
• Maintain and optimize Amazon Redshift reporting assets, determine the appropriate platform for new development, and lead migration of legacy assets to Databricks.
• Provide technical leadership through code review, modeling standards, and mentoring of analytics staff, while supporting analytical and reporting requirements through ad hoc SQL development, data validation, and Tableau development as needed.
• Other duties as assigned.

Competencies:

• Analytical Thinking
• Technical Leadership & Mentoring
• Data Governance & Stewardship
• Business Partnership
• Problem Solving
• Continuous Improvement
• Communication & Influence
• Quality & Accuracy

Skills:

• Advanced SQL, including complex joins, window functions, common table expressions (CTEs), incremental processing, and performance tuning.
• Python programming for data transformation, automation, and testing using PySpark and/or pandas.
• Databricks expertise including Delta Lake, Databricks SQL, notebooks, Workflows, declarative pipelines, Unity Catalog, and Medallion Architecture.
• Semantic and metric layer design, governance, and change management.
• Dimensional data modeling, star schema design, slowly changing dimensions, and metric development.
• Amazon Redshift administration and optimization.
• Tableau development and dashboard design.
• Git-based version control and development practices.
• Natural language analytics and AI-enabled data platforms.
• Establishing modeling standards, naming conventions, and code review practices for a team.
• Ability to translate business requirements into scalable data solutions and communicate technical concepts to non-technical and executive audiences.

Education & Experience Requirements:

Education:

Bachelor's degree in Computer Science, Information Systems, Data Analytics, Statistics, Mathematics, or a related field.

Experience:

• Seven (7) to ten (10) years of experience in data, business intelligence, or analytics disciplines, including five (5) or more years building and maintaining production data models and datasets consumed by business intelligence tools and business users in a cloud data warehouse or Lakehouse environment.
• Experience developing, governing, and maintaining semantic or metric layers supporting enterprise reporting and analytics.
• Experience with Databricks, SQL, Python, dimensional data modeling, and data governance practices.
• Experience establishing modeling standards, conducting code review, and mentoring data professionals.

Certifications:

• N/A

Preferred Experience Requirements:

Education:

Master's Degree

Experience:

• Experience with Databricks metric views and supporting Databricks AI Genie Agents or similar natural language analytics platforms.
• Experience migrating legacy data warehouse environments, including Amazon Redshift, to modern Lakehouse architectures.
• Higher education experience supporting enrollment, retention, student lifecycle, academic operations, or related functions.
• Experience with PeopleSoft, D2L, Salesforce, and FERPA-regulated data.
• Experience with dbt or comparable transformation frameworks.
• Advanced Tableau dashboard and visualization development.

Certifications:

• Databricks, Tableau, AWS, or other relevant analytics and cloud platform certifications.

All submissions should include a cover letter and resume.

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.

Workplace Accommodations:

The University of Maryland Global Campus Global Campus (UMGC) is committed to creating and maintaining a welcoming and inclusive working environment for people of all abilities. UMGC is dedicated to the principle that no qualified individual with a disability shall, based on disability, be excluded from participation in or be denied the benefits of the services, programs, or activities of the University, or be subjected to discrimination. For information about UMGC’s Reasonable Workplace Accommodation Policy or to request an accommodation, applicants/candidates can contact Employee Accommodations via email at [email protected]. 

Benefits Package Highlights:

• Generous Time Off: Enjoy 22 days of paid vacation, 15 days of sick leave, 3 personal days, and 16 paid holidays (17 during general election years). For part-time employees, time off rates will be prorated based on the number of hours worked.

• Comprehensive Health Coverage: Access to health care, medical with vision, dental, and prescription plans for both individuals and families, effective from the 1st of the month following your hire date.

• Insurance Options: Term Life Insurance, Accidental Death and Dismemberment Insurance, and Long-Term Disability (LTD) Insurance. Part-time employees working less than 0.5 FTE are not eligible for LTD.

• Flexible Spending Accounts: Available for medical and dependent care expenses.

• Retirement Plans: Choose between the Optional Retirement Program (ORP) or the Maryland State Retirement and Pension System (MSRPS).

• Supplemental Retirement Plans: include 401(k), 403(b), 457(b), and various Roth options. The university does not provide matching funds.

• Tuition Remission: Immediate availability for Regular Exempt Staff. Spouses and dependent children are eligible for undergraduate tuition remission after two years of service. NOTE: For part-time employees (at least 50 percent of the time), tuition remission benefits are prorated.

Hiring Range: