Senior Data Engineer

YOUR IMPACT 

Own your opportunity to work with the largest government agency in the nation. Make an impact by advancing the Department of War’s mission to keep our country safe and secure. 

OUR COMPANY 

Iron EagleX (IEX), a wholly owned subsidiary of General Dynamics Information Technology (GDIT), delivers agile IT and Intelligence solutions. Combining small-team flexibility with global scale, IEX leverages emerging technologies to provide innovative, user-focused solutions that empower organizations and end users to operate smarter, faster, and more securely in dynamic environments.  

JOB DESCRIPTION 

Iron EagleX is seeking a Senior Data Engineer to support our Data Analytics team in Crystal City, VA. In this role, you will design, build, and operate data pipelines that ingest, store, and process high-volume, multi-source data primarily for enterprise analytics, reporting, and decision-support use cases. You will partner with analysts, data scientists, and software engineers to create analytics-ready datasets, curated data models, and scalable storage layers. 

MEANINGFUL WORK AND PERSONAL IMPACT 

As a Senior Data Engineer, you will turn raw, multi-source data into reliable, high-performance datasets that directly enables access to trusted data for visualization, advanced analytics, and AI processing. Your work will make it faster and easier for teams across engineering, analytics, and product groups to develop, deploy, and improve data-driven capabilities by ensuring datasets are accurate, accessible, and ready for downstream consumption. 

JOB DUTIES (INCLUDE BUT ARE NOT LIMITED TO) 

• Design, develop, and implement scalable data pipelines and ETL processes using Apache Airflow, with a focus on analytics-ready data. 

• Build and tune search and retrieval capabilities using ElasticSearch/OpenSearch, including indexing strategies, schema mappings, and relevance/performance optimization. 

• Enable performant data access for analytics, reporting, and downstream applications by optimizing data access patterns, caching approaches, and index refresh strategies. 

• Collaborate with analytic teams to define requirements, schemas, metrics, and interfaces for downstream consumption. 

• Use Git for version control, peer code reviews, CI/CD workflows, and reproducible pipeline deployments across environments. 

• Operate within Linux environments and perform performance tuning across pipeline components, storage layers, and compute resources. 

REQUIRED SKILLS: