Senior Data Engineer; FedD

AI Engineering | Forward Deployed Engineering

Defense Unicorns is seeking a senior Data Engineer to embed with a government team and its technology partners building an emerging AI-powered engineering ecosystem.

This role will focus on making enterprise data usable, discoverable, governed, and accessible to AI models, agents, and mission applications. The engineer will work across data ingestion, transformation, storage, metadata, APIs, search, vector and graph technologies, and the interfaces between the data layer and AI workloads.

The ideal candidate is a hands-on data engineer who can operate across the full data lifecycle and understands that data availability and integration are often the primary blockers to delivering AI capabilities. They should be comfortable entering an evolving architecture, learning unfamiliar systems quickly, working directly with commercial technology partners, and solving difficult problems involving data quality, lineage, access, performance, and security.

This is not a traditional analytics or business intelligence role. The focus is on building the data foundations and repeatable patterns that allow AI and agentic capabilities to access trusted data and move from prototype to production in secure and classified environments.

• Design, build, and maintain reliable data pipelines that ingest, transform, validate, and deliver data for AI models, agents, and mission applications.
• Integrate structured and unstructured data sources into enterprise data services, including relational, document, vector, and graph-oriented technologies.
• Work closely with AI/agent engineers to make data discoverable and usable for RAG, semantic search, model context, and tool-enabled agent workflows.
• Develop repeatable data ingestion and transformation patterns using Python, SQL, APIs, event-driven architectures, and workflow/orchestration technologies.
• Establish data quality, validation, provenance, lineage, and metadata practices so downstream users and AI systems can trust the information they consume.
• Design data access patterns that enforce appropriate identity, authorization, classification, and security boundaries while minimizing unnecessary friction for developers and mission users.
• Collaborate with platform engineers to operationalize data services within Kubernetes/Open Shift environments and integrate them into CI/CD and Git Ops workflows.
• Help integrate enterprise data capabilities such as relational stores, JSON/document data, vector search, graph data, advanced analytics, and RAG services into the broader platform architecture.
• Troubleshoot end-to-end data issues spanning source systems, pipelines, storage, APIs, identity, networking, platform services, and AI applications.
• Work directly with government engineers and commercial technology partners to resolve data dependencies and remove blockers to mission delivery.
• Develop documentation, data contracts, schemas, architecture decision records, runbooks, and operational standards that make successful patterns repeatable across environments.
• Identify recurring data engineering challenges that can be standardized, automated, or productized rather than repeatedly solved through manual engineering.
• Operate effectively in a fast-moving, ambiguous environment where data sources, architectures, security requirements, and mission priorities will continue to evolve.

• Active TS/SCI clearance.
• 7+ years of experience in data engineering, data platform engineering, or a closely related field.
• Strong proficiency with SQL and Python for data processing, automation, and integration.
• Hands-on experience building and operating production data pipelines and…