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Data Engineer

Redbeard SolutionsBoston, MA🇺🇸United StatesPosted 19 Aug 2026

Why This Role Stands Out

This hybrid Data Engineer role offers a fantastic opportunity to shape an innovative AI platform, leveraging your expertise in Python and cloud-native architectures to build scalable data solutions. If you have 5+ years of experience and thrive in collaborative environments with competitive compensation up to $175,000, you'll be a great fit for this impactful position. Apply now to join a forward-thinking team and contribute to cutting-edge technology development.

Quick Overview

Salary
$165k - $175k/yr
Work Type
Hybrid
Level
Mid Senior

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 Google Cloud Platform 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 Google Cloud Platform 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

Skills

Docker
Neo4j
AWS
Azure
Data Pipeline
Generative AI
GitHub Actions
Google Cloud
Python

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