Analytics Engineer

The Analytics Engineer builds and maintains the analytics-ready layers of the University's Databricks Lakehouse, transforming curated data into business-ready models and contributing to the semantic layer that defines institutional metrics. Working within established modeling standards, this role delivers data products that support traditional reporting, AI-powered analytics, and natural language query capabilities, and helps maintain legacy reporting environments. Strong SQL and Python proficiency are required.

Duties and Responsibilities:

* Build and maintain Gold and Platinum layer data models in Databricks following established design patterns, transforming curated data into business-ready and consumption-ready objects using SQL and Python, orchestrated through Databricks Workflows and declarative pipelines.
* Develop and maintain semantic layer objects using Databricks metric views, implementing approved institutional metric definitions and documenting them clearly for business consumers.
* Prepare and maintain the datasets, metadata, descriptions, and example queries that support Databricks AI Genie Agents and AI/BI dashboards; test agent responses against expected results and escalate issues requiring model changes.
* Test, validate, and reconcile modeled results against systems of record; investigate discrepancies, document findings, and maintain data lineage and catalog documentation in Unity Catalog.
* Maintain, troubleshoot, and optimize Amazon Redshift reporting assets, supporting ongoing business needs and migration initiatives to Databricks.
* Support analytical and reporting requirements through ad hoc SQL development, data validation activities, and Tableau dashboard development and maintenance.
* Other duties as assigned.

Competencies:

* Analytical Thinking
* Quality & Accuracy
* Data Governance & Stewardship
* Problem Solving
* Collaboration & Communication
* Continuous Learning
* Customer Focus
* Accountability & Follow-Through

Skills:

* Strong SQL, including joins, aggregations, window functions, common table expressions (CTEs), and query troubleshooting.
* Python programming for data transformation, automation, and testing using PySpark and/or pandas.
* Working knowledge of Databricks including Delta Lake, Databricks SQL, notebooks, Workflows, and Medallion Architecture.
* Dimensional data modeling fundamentals, including star schema concepts, fact and dimension tables, and definition of grain and keys.
* Familiarity with semantic and metric layer concepts and with documenting metric definitions.
* Amazon Redshift SQL development and troubleshooting.
* Tableau development and dashboard design.
* Git-based version control and development practices.
* Ability to interpret business requirements, ask clarifying questions, and communicate technical concepts to non-technical audiences.  

Education & Experience Requirements :

Education:

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

Experience:

* Three (3) to five (5) years of experience building and maintaining production data models, datasets, or reporting assets consumed by business intelligence tools and business users.
* Experience writing production SQL against a cloud data warehouse or Lakehouse platform.
* Experience working within an established data architecture and following defined modeling, testing, and documentation standards.

Certifications:

* N/A  

Preferred Experience Requirements:

Education:

Bachelor's Degree

Experience:

* Hands-on experience with Databricks, including Delta Lake, Databricks SQL, and Workflows within a Medallion Architecture.
* Experience contributing to semantic or metric layer development.
* Exposure to AI-enabled or natural language analytics platforms such as Databricks AI Genie Agents.
* Higher education experience supporting enrollment, retention, student lifecycle, academic operations, or related functions.
* Experience with People Soft, D2L, Salesforce, or FERPA-regulated data.
* 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,…