Senior Data Engineer

General Dynamics Information Technology is a global technology and professional services company that delivers consulting and mission services to various U.S. government agencies. As a Senior Data Engineer, you will design and implement data pipelines and solutions to support enterprise analytics and AI applications, collaborating with cross-functional teams to drive innovation and mission impact.

Responsibilities:

• 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

Requirements:

• Education: Bachelor's degree in Computer Science/Engineering, Data Science, or a related field
• Experience: 10+ years of experience delivering production-grade data engineering across databases, data integration, data services, and data governance
• 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
• 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