Quick overview
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
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).
Working Conditions
- Happy - Be Infectious. Happiness multiplies and creates a positive and connected environment where motivation and satisfaction have an outsized effect on everything we do.
- Helpful - Be Supportive. Being helpful is the foundation of teamwork, resulting in a supportive atmosphere where collaboration flourishes, and collective success is celebrated.
- Honest - Be Trustworthy. Honesty serves as our compass, ensuring transparent communication and ethical conduct, essential to who we are and the complex domains we support.
- Humble - Be Grounded. Success is not achieved alone, humility ensures a culture of mutual respect, encouraging open communication, and a willingness to learn from one another and take on any task.
- Hungry - Be Eager. Our hunger for excellence drives an insatiable appetite for innovation and continuous improvement, propelling us forward in the face of new and unprecedented challenges.
- Hustle - Be Driven. Hustle is reflected in our relentless work ethic, where we are each committed to going above and beyond to advance the mission and achieve success.
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