Data Engineer

Agile Defense • Omaha, NE

3d • 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 collaborates with data scientists, analysts, and other stakeholders to understand data requirements and support efficient data flow across platforms. It also develops, deploys, and maintains low-latency streaming solutions using technologies such as Apache Kafka, Flink, or Spark Streaming.

The Data Engineer optimizes and automates workflows, oversees data models and schema designs, implements data quality and validation measures, and monitors and troubleshoots system performance. The role also keeps current with data engineering practices and tools, recommends infrastructure improvements, and mentors junior data engineers. The position is onsite in a SCIF in STRATCOM and requires Top Secret/SCI clearance.

Requirements

• Top Secret/SCI clearance required.
• Typically, a 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 year of required education.
• At least 5 years of experience in data engineering or software engineering, with 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.

Nice To Haves

• A 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, or PySpark.
• Experience developing machine learning models from training through deployment using tools and libraries such as scikit-learn, TensorFlow, XGBoost, or MLflow.
• Familiarity with MLOps, API development, and secure cloud-based environments such as AWS, Azure, or Palantir Foundry.

Responsibilities

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

What This Job Offers

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