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Analytics Engineer

University of Maryland Global Campus LogoUniversity of Maryland Global Campus
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Salary

$110,000.00 - $125,000.00

Location

Adelphi, MD

Posted

Today

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 and 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 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.

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