Data Engineer

Data Engineer role focused on designing, building, and maintaining scalable ETL/ELT pipelines and low-latency streaming solutions for analytics and reporting.

Responsibilities

• Design, build, and maintain scalable, reliable, efficient data pipelines (ETL/ELT) to extract, transform, and load data from multiple sources into data warehouses, data lakes, and other storage systems
• Partner with data scientists, analysts, and other stakeholders to align on data needs and ensure efficient data flow across platforms and systems
• Develop, deploy, and maintain real-time streaming solutions to deliver data with low latency using technologies such as Apache Kafka, Flink, or Spark Streaming
• Optimize and automate data workflows to improve efficiency, reliability, and support for increasing data volumes
• Support data modeling and schema design to enable accurate, accessible, and high-performance storage for analytics and reporting
• Implement data validation, monitoring, and error-handling to ensure data quality, integrity, and consistency
• Monitor and troubleshoot performance bottlenecks affecting data processing and data access
• Track emerging trends and best practices in data engineering and recommend tools, technologies, and methods to strengthen existing infrastructure
• Mentor and guide junior data engineers, reinforcing engineering best practices and collaboration in a high-performance team environment

Requirements

• Strong knowledge of data validation, model testing, and performance evaluation techniques
• Experience with data visualization and storytelling using Tableau, Plotly, or Matplotlib
• Strong technical communication skills, including the ability to explain complex concepts to non-technical audiences

Preferred Skills

• 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 building ML models from training through deployment using scikit-learn, TensorFlow, XGBoost, and MLflow
• Familiarity with MLOps, API development, and secure cloud environments such as AWS, Azure, and Palantir Foundry

Technologies

• Apache Kafka, Flink, Spark Streaming
• Tableau, Plotly, Matplotlib
• Python, SQL, Spark, Databricks, PySpark
• scikit-learn, TensorFlow, XGBoost, MLflow
• AWS, Azure, Palantir Foundry

Education and Experience

• Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related field
• Typically requires 5+ years of experience in data engineering or software engineering, including demonstrated experience designing and managing complex data pipelines
• Equivalent relevant work experience may substitute for education (each year of work experience may replace each year of education required)
• Masters degree preferred

Working Conditions

• Onsite in a SCIF in STRATCOM
• Location: Omaha, NE

Core Values

• Happy - Be Infectious
• Helpful - Be Supportive
• Honest - Be Trustworthy
• Humble - Be Grounded
• Hungry - Be Eager
• Hustle - Be Driven