Data Engineer

Booz Allen Hamilton•Honolulu, HI

2d•$99,000 - $225,000•Remote

About The Position

As a data engineer, you know that organizing data can yield pivotal insights when it’s gathered from disparate sources. We need an experienced data professional like you to help our clients find answers in their data to impact important missions, from fraud detection to cancer research to national intelligence. As a data engineer at Booz Allen, you’ll use your expertise to help build advanced technology solutions and lead data engineering activities on some of the most mission-driven projects in the industry. You’ll guide data engineering activities by overseeing the development and deployment of pipelines and platforms that organize and make disparate data meaningful. Here, you’ll mentor a multi-disciplinary team of analysts, data engineers, developers, and data consumers in a fast-paced, agile environment. You’ll use your expertise in analytical exploration and data examination while you oversee the assessment, design, building, and maintenance of scalable platforms for your clients. Work with us to use data for good. Join us. The world can’t wait.

Requirements

10+ years of experience architecting and delivering AI enabled mission or enterprise systems, including data integration, secure compute environments, and operator facing applications in restricted or classified settings
10+ years of experience designing and deploying data pipelines, ontologies, and application workflows on platforms such as Palantir Foundry or Gotham, including air gapped, degraded connectivity, or multiclassification environments
10+ years of experience developing secure analytics ecosystems, including log pipelines, monitoring frameworks, operational dashboards, or intelligence fusion platforms in greenfield or legacy modernization efforts
10+ years of experience implementing DevSecOps practices, including containerization, orchestration, CI/CD, and automated testing within constrained or limited toolchain environments
10+ years of experience integrating AI/ML capabilities into production workflows or operator tooling, such as LLM enabled assistants, model augmented decision aids, or automation solutions
10+ years of experience making architectural tradeoffs under constrained mission conditions, including limited infrastructure, fragmented networks, evolving requirements, or high-pressure operational timelines
Experience rapidly learning unfamiliar technologies, developing hands on proficiency, and guiding engineering teams through full lifecycle implementation
Experience communicating architectural decisions and solution impacts to engineering teams, government clients, and senior nontechnical stakeholders
Secret clearance
Bachelor’s degree

Nice To Haves

Experience supporting multi cloud, multi enclave, or multiclassification architectures, including environments spanning NIPR, SIPR, JWICS, or coalition networks
Experience contributing to major defense programs or largescale systems integration efforts, including navigating acquisition, compliance, or bureaucratic constraints
Experience supporting DoD installations, operational units, or C2 systems in environments with incomplete documentation, degraded systems, or inconsistent technical baselines
Experience developing agentic workflows, automation pipelines, or custom tooling that improved engineering velocity or reduced operator burden
Experience serving as a senior technical lead or architect responsible for end-to-end solution delivery
Experience working on tiger teams, flyaway teams, or rapid response engineering missions requiring accelerated delivery under complex conditions
Top Secret clearance
Architecture frameworks
Certifications such as AWS, Palantir Foundry or Gotham, or Kubernetes Certification

Responsibilities

Overseeing the development and deployment of pipelines and platforms that organize and make disparate data meaningful.
Mentoring a multi-disciplinary team of analysts, data engineers, developers, and data consumers in a fast-paced, agile environment.
Overseeing the assessment, design, building, and maintenance of scalable platforms for clients.
Architecting and delivering AI enabled mission or enterprise systems, including data integration, secure compute environments, and operator facing applications in restricted or classified settings.
Designing and deploying data pipelines, ontologies, and application workflows on platforms such as Palantir Foundry or Gotham, including air gapped, degraded connectivity, or multiclassification environments.
Developing secure analytics ecosystems, including log pipelines, monitoring frameworks, operational dashboards, or intelligence fusion platforms in greenfield or legacy modernization efforts.
Implementing DevSecOps practices, including containerization, orchestration, CI/CD, and automated testing within constrained or limited toolchain environments.
Integrating AI/ML capabilities into production workflows or operator tooling, such as LLM enabled assistants, model augmented decision aids, or automation solutions.
Making architectural tradeoffs under constrained mission conditions, including limited infrastructure, fragmented networks, evolving requirements, or high-pressure operational timelines.
Rapidly learning unfamiliar technologies, developing hands on proficiency, and guiding engineering teams through full lifecycle implementation.
Communicating architectural decisions and solution impacts to engineering teams, government clients, and senior nontechnical stakeholders.