Company Overview

Orbis is a technology company that delivers sovereign intelligence and decision capabilities to the United States Government and its allies. We convert complex information and operational systems into decisive outcomes, giving public institutions and critical enterprises the tools to move faster, see clearer, and act first in an increasingly contested world.

We are not a consulting firm and not a systems integrator. Every Orbis team is built around practitioners who have operated at the mission edge, and every engagement is judged on one thing: whether it produces working capability, not slide decks. Solutions forged from experience; that is how we build, and it is how we hire.

Job Summary

We are looking for a Data Engineer to help build, deploy, and sustain data pipelines and supporting applications for federal intelligence programs. This is a growth role: broad exposure across the data life cycle matters more to us than deep specialization in any one technology. The right candidate is curious, adaptable, and ready to pick up new tools as the mission requires, with a clear path to greater technical ownership over time.

Travel: The engineer works primarily on-site in customer spaces, must be available for meetings across the Washington Metro Area, and may work occasionally from Orbis offices or home.

Key Responsibilities

Data Pipelines: Build and sustain ingestion pipelines that pull structured and unstructured data from feeds, batch loads, and external systems.
Delivery: Translate requirements from analysts and end users into working data flows and supporting application features.
Application Support: Build and maintain supporting interfaces and server-side logic as needed to expose or operate on pipeline data.
AI/Agentic Support: Support the architecture, integration, and validation layers behind AI agent and retrieval-driven applications.
Deployment & Sustainment: Package, deploy, and sustain containerized pipelines and applications in cloud and accredited environments, including air-gapped enclaves.
Testing & Support: Debug issues, run automated and functional tests, and resolve user-reported problems.
Collaboration: Work with product owners, analysts, and senior engineers in an agile environment.

Required Qualifications

Clearance: Active TS/SCI clearance with a poly.
Experience: 2–5 years of experience in data engineering, software development, or a related technical role working with data and applications.
Technical Skills: Intermediate experience with Python and SQL.
Data & Application Integration: Basic experience working with APIs, connecting different systems and data sources, and building or supporting data pipelines.
Linux & Containers: Basic hands-on experience running applications or data tools in a Linux environment; experience with containers is helpful.
Adaptability: Able to learn new programming languages, tools, and technologies as needed. We value problem-solving and a willingness to learn over deep expertise and experience in any specific technology.
Coachability & Growth: Open to learning application development and taking on new responsibilities. We're looking for someone with strong learning instincts who responds well to feedback and can grow with the role.
Familiarity using Claude Code, Copilot, Codex or other AI coding tool.

Desired Qualifications

End-to-end ownership of a data pipeline or application, from initial build through deployment and sustainment.
Relational and embedded analytical databases.
CI/CD pipelines and automated build tooling.
Deployment into GovCloud, secure enclaves, or other accredited or isolated environments.
Agentic AI Architecture: Working familiarity with how models, tools, retrieval, and validation layers fit together in modern AI agent applications.
Configuration-Driven Design: Comfort externalizing business logic into configuration files rather than hard-coding it into the application.
Familiarity with JavaScript or TypeScript and Git is a plus. A GitHub profile with examples of your work is welcome.