Data Engineering Student Intern… at University of… · Charlotte…

Summary: 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, working with production enterprise data and modern cloud data tooling. 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 Required Qualifications: - 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 Preferred Qualifications: - 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 Required Skills: SQL, Databases, Data modeling, Data engineering, Microsoft Fabric, Data warehousing concepts, Enterprise data warehouse, Data pipelines, Lakehouse schemas, Warehouse schemas, Data transformation, Data normalization, Data validation, learn new tools quickly Benefits: Mentorship from experienced data, analytics, and IT professionals, Direct experience building and operating an enterprise‑grade data platform, Exposure to institutional data governance and integration at a major public university, Practical experience with Microsoft Fabric in a production environment, A portfolio‑worthy project with real, lasting institutional impact