Design, build, and maintain data pipelines in Microsoft Fabric to ingest data from multiple Law School and University source systems
Develop and manage Lakehouse and/or Warehouse schemas, including fact and dimension tables
Perform data transformation, normalization, and validation using SQL and Fabric-native tools
Help align Law School data structures with University enterprise data models and standards
Document data schemas, lineage, and transformation logic to support long-term maintainability
Assist with data quality checks, reconciliation, and troubleshooting
Collaborate with analytics and application stakeholders to ensure datasets meet downstream needs

Requirements

Current UVA undergraduate or graduate student
Strong SQL skills (querying, joins, aggregations, and data transformations)
Coursework or hands-on experience with databases, data modeling, or data engineering
Comfort working with structured data and relational schemas
Ability to learn new tools quickly and work independently with guidance
Experience with Microsoft Fabric, Azure Synapse, or similar modern data platforms (preferred)
Familiarity with data warehousing concepts (fact/dimension models, ETL/ELT patterns) (preferred)
Exposure to analytics pipelines or cloud-based data lakes (preferred)
Experience working with large or messy real-world datasets (preferred)
Interest in enterprise analytics, reporting, or data platform architecture (preferred)

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

SQLdata transformationdata normalizationdata validationdata modelingdata engineeringdata warehousingETLELTdata pipelines

Soft Skills

ability to learn quicklyindependent workcollaborationtroubleshootingdocumentation