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# Data Engineer

- **Company:** General Dynamics Information Technology
- **Location:** Fairview Park, OH, United States (Remote available)
- **Experience:** Experienced
- **Salary:** $81,349.0 - $105,800.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Biometrics, Cloud Computing, Cloud Engineering, Databases, Data as a Services, Data Architecture, Information Engineering, Data Governance, Data Integration, Python (Programming Language), Metadata, NoSQL, Performance Tuning, Systems Development Life Cycle, Cloud Services, Requirements Management, Software Engineering, SQL Databases, Data Streaming, Unstructured Data, Enterprise Data Management, Scripting, Enterprise Software Applications, Indexer, Information Technology, Data Management, Virtual Agents, Oracle Cloud Infrastructure, Data Pipelines, Programming Languages
- **Published:** September 8, 2026
- **Apply:** https://www.careerbuilder.com/job-details/data-engineer-fairview-park-oh--512c18b2-5951-4c6d-a768-97150f0ac2d1

## About the Role

Data Governance, Python Software Development, SQL Query Development, Unstructured Data, 2 + years of related experience, * Education: Bachelor's degree in Computer Science/Engineering, Data Science, or a related field

 * Experience: 2+ years of experience delivering production-grade data engineering across databases, data integration, data services, and data governance
 * Role requirements:
 + Proficiency in programming languages (Python or Java) and databases (SQL and NoSQL).
 + Experience with enterprise-scale data architectures and cloud data platforms such as Azure (preferred), OCI, or AWS.
 + Strong collaboration and communication skills in cross-functional enterprise environments.
 * Preferred Skills and Abilities:
 + 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: Falls Church, VA (Hybrid, with the expectation the selected individual will work three (3) days per week in office)
 * US Person required, Accidental Death and Dismemberment (AD&D), Amazon Web Services (AWS), Application Programming Interface (API), Artificial Intelligence (AI), Artificial Intelligence (AI) Agents, Best Practices, Biometrics, Cloud Architecture, Cloud Computing, Communication Skills, Computer Science, Contract Requirements, Cost Control, Cross-Functional, Data Management, Data Quality, Data Science, Defense Intelligence, Documentation, Ecosystems, Enterprise Data Integration, Finance, Government, Health Plan, Insurance, Intelligence Community, Java, Legal, Microsoft Windows Azure, Military, NoSQL, Performance Tuning/Optimization, Product Support, Productivity Management, Professional Services, Programming Languages, Python Programming/Scripting Language, Requirements Management, SQL (Structured Query Language), Scalable System Development, Service Delivery, Software Development, Software Engineering, Structured Data, Supply Chain, Team Player, Technical Delivery, Testing, United States Citizen, Unstructured
Data, Use Cases, Willing to Travel

## Description

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


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