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Intern - Year Round (Data Quality Engineering)

Company:
Navy Federal Credit Union
Location:
Vienna, VA, 22181
Posted:
April 19, 2026
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Description:

Join Navy Federal as an intern to gain valuable insights into our business, technology, resources, and procedures.

This year-round internship offers flexible hours (Full-Time or Part-Time) based on your school schedule.

You will support evolving Data Quality capabilities and improving the quality of NFCU data assets in Azure Cloud; this includes Enterprise Data Lake, Data Warehouse, and Data Hubs.

This role will also interact with multiple teams in accomplishment of their assignments and provide professional execution of day-to-day tasks and special projects while working within established standards, policies, and procedures.

* A requirement of this position is you must be currently enrolled in college level courses or a degree-seeking program throughout the duration of the internship.

Please upload your transcripts by adding them to the "Intern Proof of Enrollment" section of the application.

* Improve bespoke framework (Databricks) that controls and monitors Data Quality in Azure Cloud * Support enabling Data Quality check and alert for batch data service and data streaming services * Collaborate with the team to evolve standards and best practices for Data Quality engineering * Support enabling Data Quality metrics that provides a summary drill down view of Data Quality scores for the business and leadership * Perform other duties as assigned Required Qualifications * Currently pursuing a degree from an accredited college or university, preferably in Computer Science, Data Engineering or related field * Ability to apply Data Quality dimensions and principles * Ability to work independently and collaboratively in a team environment * Strong research, analytical, and problem-solving abilities Desired Qualifications * Effective communication skills and a commitment to self-development * Hands-on experience in data processing (Databricks ETL, Azure Event Hub, Azure Functions, or similar) * Hands-on experience in Big Data environment in cloud for Enterprise Data Lake (Azure or similar), Data Warehouse (Azure Synapse or similar), and Data Hubs (Azure Cosmos DB or similar) * Hands-on experience with programming languages such as Python, SQL, or Java

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