Data Engineer

Agile Defense • Omaha, NE

1d • Onsite

About The Position

Agile Defense is hiring a Data Engineer to design, build, and maintain scalable, reliable, and efficient data pipelines that extract, transform, and load data from various sources into warehouses, lakes, and other storage systems. The role partners with data scientists, analysts, and stakeholders to understand data requirements and support efficient data flow across platforms. It also develops and maintains low-latency streaming solutions, optimizes and automates workflows, and oversees data models and schemas for accessible, high-performance analytics and reporting.

The Data Engineer ensures data quality, integrity, and consistency through validation, monitoring, and error handling; monitors and troubleshoots data-system performance; and recommends tools and methods to improve infrastructure. The role also mentors junior data engineers and promotes collaborative engineering practices. This position is onsite in a SCIF at STRATCOM in Omaha, Nebraska, and requires Top Secret/SCI clearance.

Requirements

• Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field, or equivalent relevant work experience; each year of work experience may substitute for each required year of education.
• At least 5 years of experience in data engineering or software engineering, including demonstrated experience designing and managing complex data pipelines.
• Strong understanding of data validation, model testing, and performance evaluation techniques.
• Experience with data visualization and storytelling using tools such as Tableau, Plotly, or Matplotlib.
• Excellent technical communication skills, including the ability to explain complex concepts to non-technical audiences.
• Top Secret/SCI clearance required.

Nice To Haves

• Master's degree.
• At least 4 years of experience in applied data science, machine learning engineering, or data pipeline development.
• Proficiency in Python, SQL, and distributed data frameworks such as Spark, Databricks, and PySpark.
• Experience developing machine learning models from training through deployment using tools and libraries such as scikit-learn, TensorFlow, XGBoost, and MLflow.
• Familiarity with MLOps, API development, and secure cloud-based environments such as AWS, Azure, and Palantir Foundry.

Responsibilities

• Design, build, and maintain scalable, reliable, and efficient ETL/ELT data pipelines.
• Collaborate with data scientists, analysts, and other stakeholders to understand requirements and support data flow across platforms and systems.
• Develop, deploy, and maintain real-time, low-latency data streaming solutions.
• Optimize and automate data workflows to improve efficiency, reliability, and capacity for growing data volumes.
• Oversee data model and schema development for accurate, accessible, high-performance analytics and reporting.
• Implement data validation, monitoring, and error-handling mechanisms to ensure data quality, integrity, and consistency.
• Monitor and troubleshoot data-system performance bottlenecks and resolve processing or data-access issues.
• Stay current with data engineering trends and recommend tools, technologies, and methods to improve infrastructure.
• Mentor junior data engineers, promote engineering best practices, and foster a collaborative team environment.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level