Data Architecture & Governance Intern

Leidos

21h

About The Position

Are you curious about how large organizations turn raw data into trusted, usable information? Join our Chief Data & Analytics Office (CDAO) this summer as a Data Architecture & Governance Intern, where you’ll get hands-on experience working with enterprise data platforms, governance tools, and modern analytics practices. You’ll collaborate with data architects, data engineers, data scientists, and product owners to help design, document, govern, and improve the data assets that power decision-making across the enterprise. This role offers real-world exposure to data modeling, metadata management, data quality, and emerging technologies like APIs and AI agents—all while contributing to meaningful, production-relevant work. Primary Responsibilities: As a member of the Data Architecture and Governance team, the intern will assist with a variety of initiatives, including: Supporting data modeling and data product teams with documentation, metadata enrichment, and asset organization Assisting with data governance activities, including business glossary management, data domain alignment, and stewardship workflows Building Collibra content and business community views Helping synchronize the Collibra DEV environment to make it closer to production (views, glossary terms, and data assets) to support testing and development Creating and updating standard operating procedures (SOPs) and training materials, including short how-to guides and videos Writing and validating Snowflake SQL queries to support data quality checks, analysis, and governance use cases Assisting with data quality initiatives, including profiling, rule definition, and issue tracking Collaborating with engineers and data scientists to, build one or two simple APIs or data integrations. Participating in team meetings, design discussions, and governance forums to gain exposure to enterprise data decision-making

Requirements

Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Data Science, Information Systems, Engineering, Analytics, or a related field
Fundamental understanding of data concepts i.e., data structures and data design (tables, schemas, metadata, data quality, data modeling basics)
Experience with or coursework involving SQL
Strong analytical and problem-solving skills
Ability to document processes clearly and communicate technical ideas to both technical and non-technical audiences
Comfortable working in a collaborative, team-based environment
Interest in data governance, data architecture, analytics, or enterprise data platforms
US citizenship required

Nice To Haves

Exposure to data governance or metadata management tools.
Familiarity with Data Modeling Tools.
Familiarity with cloud data platforms, especially Snowflake
Experience with Python, REST APIs, or scripting
Coursework or projects involving data modeling, data engineering, or analytics
Interest in AI/ML concepts, automation, or agent-based tools
Strong organizational skills and attention to detail
Curiosity about how data is managed at scale in large, complex organizations.

Responsibilities

Supporting data modeling and data product teams with documentation, metadata enrichment, and asset organization
Assisting with data governance activities, including business glossary management, data domain alignment, and stewardship workflows
Building Collibra content and business community views
Helping synchronize the Collibra DEV environment to make it closer to production (views, glossary terms, and data assets) to support testing and development
Creating and updating standard operating procedures (SOPs) and training materials, including short how-to guides and videos
Writing and validating Snowflake SQL queries to support data quality checks, analysis, and governance use cases
Assisting with data quality initiatives, including profiling, rule definition, and issue tracking
Collaborating with engineers and data scientists to, build one or two simple APIs or data integrations.
Participating in team meetings, design discussions, and governance forums to gain exposure to enterprise data decision-making