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., * 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.

• 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., Bachelor’s Degree, * 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 PeopleSoft, D2L, Salesforce, or FERPA-regulated data.
• Advanced Tableau dashboard and visualization development.

Certifications:

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

• 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.