Data Engineer

Key Responsibilities

• Design, develop, and maintain scalable data pipelines to ingest, transform, and curate logistics, maintenance, and supply chain data from multiple USMC systems.
• Implement robust ETL/ELT workflows to support analytics, reporting, and data warehousing initiatives.
• Collaborate with data analysts, software engineers, and system integrators to ensure high-quality data delivery for operational and strategic use cases.
• Optimize database performance, manage data models, and ensure data accessibility and consistency across environments.
• Work with NIWC Atlantic and USMC stakeholders to translate logistics data requirements into technical solutions.
• Integrate data from authoritative USMC logistics systems such as GCSSMC, TLS, and other readiness and sustainment datasets.
• Ensure compliance with DoD cybersecurity, RMF, and data governance standards when designing and deploying solutions.
• Support the development of dashboards, APIs, and analytics tools that improve supply chain visibility and asset readiness.
• Troubleshoot data issues, perform root cause analysis, and implement corrective actions to maintain data integrity.

Requirements

• Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related field (or equivalent experience).
• Handson experience with SQL, relational databases, and data modeling.
• Proficiency with modern ETL/ELT tools and data pipeline technologies (such as Python, Airflow, Spark, or similar).
• Experience with cloud environments (AWS, Azure, or DoD specific cloud platforms).
• Ability to work within Agile teams and collaborate with cross functional technical and government stakeholders.
• Strong understanding of data quality, integrity, and governance principles.
• Active DoD Secret Clearance (or ability to obtain and maintain one).
• Experience supporting DoD, USMC, or logistics/sustainment data systems.
• Familiarity with NIWC Atlantic processes, environments, and program expectations.
• Exposure to GCSSMC, logistics readiness systems, or maintenance/supply chain data environments.
• Experience with containerization, CI/CD pipelines, and DevSecOps concepts.
• Knowledge of RMF, cybersecurity best practices, and secure data engineering approaches.