Bachelor's degree in Computer Science, Information Systems, Data Engineering, or related field (master's preferred)
5+ years of experience in data engineering or software engineering
Strong understanding of data validation, model testing, and performance evaluation techniques
Experience with data visualization tools like Tableau, Plotly, or Matplotlib
Excellent technical communication skills for explaining complex concepts to non-technical audiences
Responsibilities
Design, build, and maintain scalable data pipelines for ETL/ELT processes
Collaborate with data scientists and analysts to ensure efficient data flow
Develop and maintain real-time data streaming solutions with low latency
Optimize and automate data workflows for reliability and efficiency
Oversee development of data models and schema designs for analytics
Ensure data quality and integrity through validation and monitoring
Mentor junior data engineers and promote best practices
Benefits
Top Secret/SCI clearance required
Opportunity to work in a collaborative, high-performance team environment
Access to cutting-edge tools and technologies
Potential for professional development and mentorship
Onsite work in a secure environment (SCIF)
Full Job Description
Requisition #: 1956
Job Title: Data Engineer
Location: Omaha, NE
Clearance Level: Top Secret/SCI required
Job Description
Design, build, and maintain highly scalable, reliable, and efficient data pipelines for extracting, transforming, and loading (ETL/ELT) data from various sources into data warehouses, data lakes, and other storage systems.
Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and ensure the efficient flow of data across various platforms and systems. Develop, deploy, and maintain real-time data streaming solutions to process and deliver data with low latency (using tools like Apache Kafka, Flink, or Spark Streaming).
Optimize and automate data workflows, ensuring that data pipelines are efficient, reliable, and capable of handling increasing data volumes.
Oversee the development of data models and schema designs to ensure accurate, accessible, and high-performance data storage for analytics and reporting.
Ensure data quality, integrity, and consistency by implementing data validation, monitoring, and error-handling mechanisms.
Monitor and troubleshoot performance bottlenecks in data systems, resolving issues with data processing and data access.
Stay current with emerging trends and best practices in data engineering, recommending new tools, technologies, and methods to enhance existing infrastructure.
Mentor and guide junior data engineers, promoting best practices in data engineering and fostering a collaborative, high-performance team environment.
Education and Background
Typically has a Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field (masters degree preferred)., and 5+ years of experience in data engineering or software engineering, with demonstrated experience in designing and managing complex data pipelines., or equivalent relevant work experience; e.g., each year of work experience may be substituted for each year of education required.
Years of Experience
5+ years
Required Skills
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, with 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.
Proficient in Python, SQL, and distributed data frameworks (e.g., Spark, Databricks, PySpark).
Experience developing ML models from training to deployment using industry-standard tools and libraries (e.g., scikit-learn, TensorFlow, XGBoost, MLflow).
Familiarity with MLOps, API development, and secure cloud-based environments (e.g., AWS, Azure, Palantir Foundry).
