Data Engineering Student Intern (Student Wage)
About The Position
The University of Virginia School of Law is seeking a Data Engineering Student Intern to support a major modernization of the Law School’s data warehouse and analytics infrastructure. This role will focus on the data engineering foundations of the project: migrating and re‑architecting the Law School’s data warehouse to integrate with the University’s enterprise data warehouse (working in coordination with the central data team), using Microsoft Fabric as the platform for ingestion, transformation, and storage. The resulting Law School data lake and curated warehouse will become the authoritative source for existing reporting, downstream applications, and new analytics development. This is a hands‑on opportunity to work with production enterprise data, modern cloud data tooling, and real‑world data governance requirements. Note: This position is intentionally focused on data engineering and platform work. Application development and front‑end reporting are out of scope for this role.
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
Nice To Haves
- Experience with Microsoft Fabric, Azure Synapse, or similar modern data platforms
- Familiarity with data warehousing concepts (fact/dimension models, ETL/ELT patterns)
- Exposure to analytics pipelines or cloud‑based data lakes
- Experience working with large or messy real-world datasets
- Interest in enterprise analytics, reporting, or data platform architecture
Responsibilities
- 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
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What This Job Offers
Job Type
Part-time
Career Level
Intern
Education Level
No Education Listed
Number of Employees
5,001-10,000 employees
