Data Engineer

Redbeard Solutions

$165K — $175K *
Aerospace & Defense
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years of data engineering experience, emphasizing cloud solutions
  • U.S. Citizenship and active Secret clearance required
  • Experience in defense or government environments involving classified data
  • Proficiency in Python for data workflows
  • Hands-on experience with AWS-based engineering, knowledge of Azure/GCP is a plus
  • Strong understanding of data modeling and ingestion frameworks
  • Experience with Neo4j and relational databases

Responsibilities

  • Design and build data ingestion and processing pipelines for AI applications
  • Develop and maintain Python data workflows, ensuring quality through testing
  • Collaborate with cross-functional teams of engineers, data scientists, and designers
  • Implement CI/CD pipelines to enhance deployment integration
  • Work across multi-cloud environments primarily using AWS
  • Utilize Docker for scalable deployments
  • Optimize data systems for generative AI applications

Benefits

  • Opportunity to work on high-impact AI platform initiatives
  • Fast-paced environment with strong technical mentorship
  • Structured development programs for continuous learning
  • Collaborative culture prioritizing innovation and diverse perspectives
  • Experience with globally distributed teams and modern engineering practices
Full Job Description
About the job Data Engineer

Job Title: Data Engineer - AI Platform

Location: Boston, Chicago, New York City, San Francisco, Silicon Valley, Washington DC

Number of openings: 1

Experience: 5+ years of professional experience as a data engineer

Salary: $165,000 - $175,000

Clearance: Secret (prefer TS)

Position Summary

We are hiring a skilled Data Engineer to contribute to the development of a sophisticated AI-powered platform that supports advanced, data-driven solutions. This role offers the opportunity to work on cutting-edge initiatives involving generative AI, large-scale data systems, and cloud-native architectures.

You will partner with a multidisciplinary team of engineers, data scientists, and product stakeholders to design and implement scalable data infrastructure. The primary focus will be enabling platform capabilities tailored for government and defense-related environments.

Key Responsibilities
  • Design and build robust data ingestion and processing pipelines to support AI and GenAI applications
  • Develop and maintain high-quality Python-based data workflows, including testing and validation
  • Collaborate with cross-functional teams including software engineers, data scientists, and UI/UX designers
  • Implement and enhance CI/CD pipelines (including GitHub Actions) to streamline deployment and integration processes
  • Work across multi-cloud environments (AWS primarily; exposure to Azure and GCP is beneficial)
  • Utilize containerization technologies (Docker) to support scalable and portable deployments
  • Contribute to the development and optimization of data systems used by generative AI applications
  • Ensure performance, reliability, and scalability of data pipelines through monitoring and diagnostics

What You'll Experience
  • Opportunity to work on high-impact AI platform initiatives
  • A fast-paced, performance-driven environment with strong technical mentorship
  • Continuous learning through structured development programs and real-world problem solving
  • A collaborative culture that values innovation, ownership, and diverse perspectives
  • Exposure to globally distributed teams and modern engineering practices
  • Competitive compensation along with a comprehensive benefits package

Required Qualifications
  • U.S. Citizenship is required
  • Prior experience supporting defense or government environments, including handling classified or sensitive data
  • Active Secret clearance required (Top Secret or higher preferred)
  • 5+ years of experience in data engineering, with a strong focus on cloud-based solutions

Technical Skills & Expertise
  • Strong proficiency in Python for data engineering and pipeline development
  • Hands-on experience with AWS-based data engineering (experience with Azure or GCP is a plus)
  • Deep understanding of data modeling, data ingestion frameworks, and pipeline architecture
  • Experience working with knowledge graphs, particularly using Neo4j, and familiarity with relational databases
  • Expertise in writing clean, maintainable, and testable code, including automation and error handling best practices
  • Practical experience with Docker and containerized workflows
  • Strong background in data pipeline performance tuning, monitoring, and troubleshooting
  • Excellent analytical and problem-solving capabilities
  • Effective communication skills and ability to collaborate within cross-functional teams

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