Revolutional delivers advanced technology solutions and mission support to federal agencies across civilian, health, and national security environments. We apply modern capabilities, including AI/ML, cloud, cybersecurity, and IT modernization to solve complex challenges, enable faster and more secure operations, and drive measurable mission outcomes. We are redefining how federal technology gets built and delivered by operating with a product mindset, prioritizing speed, ownership, and execution over bureaucracy.

Data Engineer – Cyber Risk Security Data Platforms Location: Remote Terms: Full-time Clearance: Qualified candidates must be US citizens and have the ability to obtain and maintain a Public Trust is required Travel: 0% Project Description This position supports Revolutional’s customer, the Department of Veterans Affairs (VA), as part of the Cybersecurity Transformation Program (CTP). The program is modernizing cybersecurity capabilities through data-driven platforms, cloud infrastructure, and integrated analytics pipelines. A key focus is enabling secure, scalable data infrastructure that supports cyber risk awareness, assessment, and response.

The core challenge: building and maintaining reliable data pipelines and systems that support real-time security insights while ensuring data quality, integrity, and protection. Position Description As a Data Engineer at Revolutional, you will operate as a hands-on developer responsible for building, maintaining, and optimizing data pipelines and data services that support cybersecurity operations. This is an individual contributor role where you will be writing code, developing pipelines, integrating APIs, and troubleshooting data systems daily.

You will work across cloud environments and security-focused data platforms to ensure data is accurate, reliable, and usable for downstream analytics and risk management. You are expected to go beyond basic data movement while owning data quality, pipeline reliability, and secure data handling in a production environment.

Responsibilities

Design, develop, and maintain ETL/ELT pipelines for secure data ingestion, transformation, and reporting Build and manage REST APIs and data ingestion services across systems Write production-grade code using Python and/or SQL to support data processing and automation Implement data validation, monitoring, and alerting to ensure data quality and reliability Identify and resolve schema changes, data inconsistencies, and pipeline failures Work with structured and unstructured data across multiple sources Leverage cloud platforms (AWS, Azure) for storage, compute, and data services Deploy and manage data workloads in containerized environments (Docker, Kubernetes) Support integration of data pipelines into broader DevSecOps and automation workflows Contribute to security-focused data initiatives, including data protection and risk analysis support Collaborate with engineering and security teams to support operational and analytical use cases Technical Environment Cloud platforms (AWS, Azure) Containerized environments (Docker, Kubernetes) ETL/ELT pipelines and orchestration frameworks REST APIs and data ingestion services Data validation, monitoring, and alerting tools Cybersecurity data platforms and analytics environments DevSecOps and automation-driven delivery pipelines What You Bring (

Requirements

) Baseline