Falls Church, Virginia, United States of America
15 hours ago
Data Engineer
REQ#: RQ212609Public Trust: None Requisition Type: Regular Your Impact

Own your opportunity to be at the center of GDIT’s business operations. Make an impact by collaborating across functions to make mission success achievable.

Job Description

Own your opportunity to turn data into measurable outcomes for our customers’ most complex challenges. As a Data Engineer at GDIT, you’ll power innovation to drive mission impact and grow your expertise to power your career forward. We are a fast-growing AI and Data team within the Global CIO organization at GDIT. We design and deliver enterprise-grade solutions that integrate AI, data, and human-AI collaboration workflows across key business functions (e.g., Growth, Finance, HR, Legal, and Supply Chain). We are looking for a highly skilled Data Engineer (Agentic AI) who shares a passion for delivering data engineering for agentic AI applications and building an AI-first data ecosystem foundational to enterprise AI transformation.

MEANINGFUL WORK AND PERSONAL IMPACT:

Design, build, and operate scalable end-to-end data pipelines and curated data products that support enterprise analytics and agentic AI use casesIntegrate data from enterprise systems and external sources, including structured, semi-structured, and unstructured dataDeliver reliable data services for agentic AI workflows, including APIs, retrieval/indexing, and governed context delivery for AI agentsImplement data quality, observability, and governance best practices across data pipelines and productsOptimize performance and cost across storage, compute, orchestration, and serving layersCollaborate with cross-functional teams, including business stakeholders, AI engineers, and software developers, to translate requirements into production solutions

WHAT YOU’LL NEED TO SUCCEED
Bring your expertise and drive for innovation to GDIT. The Data Engineer must have:

Education: Bachelor’s degree in Computer Science/Engineering, Data Science, or a related fieldExperience: 5+ years of experience delivering production-grade data engineering across databases, data integration, data services, and data governanceRole requirements: Proficiency in programming languages (Python or Java) and databases (SQL and NoSQL). Strong collaboration and communication skills in cross-functional enterprise environments.Preferred Skills and Abilities: Master’s degree in Computer Science/Engineering, Data Science, or a related field. Relevant certifications in Data Engineering, AI, or Cloud. Experience delivering data engineering for agentic AI applications. Experience with retrieval-based AI data foundations (document processing, metadata, embeddings, vector or hybrid search). Familiarity with agent workflows and how agents interact with data services and tools in production. Experience with lakehouse architectures and cloud data platforms such as Azure (preferred), OCI (preferred), or AWS, Experience in real-time streaming applications or other high-velocity solutions. Experience leveraging AI tools to improve data engineering productivity and quality in coding, testing, and documentation.Location: This is a hybrid position working at our GDIT facility in Falls Church, VA. Must be comfortable working (3) days a week onsite.US Persons required


GDIT IS YOUR PLACE
At GDIT, the mission is our purpose, and our people are at the center of everything we do.

Growth: AI-powered career tool that identifies career steps and learning opportunitiesSupport: An internal mobility team focused on helping you achieve your career goalsRewards: Comprehensive benefits and wellness packages, 401K with company match, and competitive pay and paid time offFlexibility: Full-flex work week to own your priorities at work and at homeCommunity: Award-winning culture of innovation and a military-friendly workplace


OWN YOUR OPPORTUNITY
Explore a career in data science and engineering at GDIT and you’ll find endless opportunities to grow alongside colleagues who share your determination for solving complex data challenges.

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