Data Engineer / Senior Data Engineer (Cloud & Modern Data Platforms)

ReefPoint Group (RPG) is a mission-driven consulting firm dedicated to improving outcomes for Veterans, service members, and federal agencies through data, technology, and strategic consulting. We partner with our clients to solve complex operational challenges, modernize enterprise systems, and transform data into actionable insights that drive mission success.

At RPG, we value curiosity, collaboration, integrity, and innovation. Our teams work alongside clients to deliver practical solutions that make a measurable impact while fostering a culture of continuous learning and professional growth.

Position Overview

ReefPoint Group is seeking Data Engineers and Senior Data Engineers to join our growing Data & AI practice. This posting is part of our Data Engineering Talent Community, supporting multiple current and upcoming opportunities across our federal client portfolio.

We're looking for engineers who enjoy solving complex data challenges, building scalable cloud solutions, and enabling advanced analytics and AI capabilities. This is an opportunity to work with modern data platforms, collaborate with multidisciplinary teams, and help organizations unlock the full value of their data.

Successful candidates will have experience designing, building, and maintaining modern data solutions using cloud platforms and enterprise data technologies. Experience with platforms such as Palantir Foundry, Databricks, Microsoft Fabric, Snowflake, Azure, AWS, or similar technologies is highly desirable.

What You'll Do

• Design, develop, and maintain scalable data pipelines and data integration solutions.
• Build and optimize cloud-based data platforms that support analytics, reporting, and operational decision-making.
• Integrate, transform, and operationalize structured and unstructured data from multiple enterprise sources.
• Develop ETL/ELT processes and automated data ingestion workflows.
• Support data modeling, data mapping, and enterprise data integration initiatives.
• Improve data quality, reliability, governance, and accessibility across enterprise environments.
• Collaborate with architects, analysts, product teams, and client stakeholders to understand business and mission requirements.
• Enable advanced analytics, artificial intelligence, and machine learning capabilities through modern data engineering practices.
• Participate in solution design, technical troubleshooting, and continuous platform improvement.
• Develop automated monitoring, validation, and quality control processes for enterprise data solutions.
• Contribute to engineering best practices, code reviews, and continuous integration/continuous deployment (CI/CD) activities.
• Stay current on emerging cloud technologies, data engineering practices, and industry trends.