CDC Foundation is hiring a
Data Engineer

Summary

Join the CDC Foundation as a Data Engineer in a remote, limited-term opportunity. The role involves designing, building, and maintaining data infrastructure for the South Dakota Department of Health's Epidemiology, Surveillance and Informatics Center (ESIC). This position is part of the Workforce Acceleration Initiative (WAI) and focuses on documenting and maintaining the case-based disease surveillance system architecture. The salary range is $103,500-$143,500 per year plus benefits.

Requirements

• Bachelor's degree in Computer Science, Information Technology, Data Science, or a related field
• 5 years of experience with project oversight
• Proficiency in programming languages commonly used in data engineering
• Experience with Microsoft Azure cloud technologies and frameworks or similar (AWS)
• Strong understanding of database systems
• Experience regarding engineering best practices such as source control, automated testing, continuous integration and deployment, and peer review
• Knowledge of data warehousing concepts and tools
• Experience with cloud computing platforms
• Expertise in data modeling, ETL (Extract, Transform, Load) processes, and data integration techniques
• Solid understanding of FHIR and API-based architectures
• Familiarity with agile development methodologies, software design patterns, and best practices
• Strong analytical thinking and problem-solving abilities
• Excellent verbal and written communication skills
• Experience working with project management and tracking software (e.g., JIRA and DevOps)
• Flexibility to adapt to evolving project requirements and priorities
• Outstanding interpersonal and teamwork skills
• Experience working in a virtual environment with remote partners and teams
• Proficiency in Microsoft Office

Responsibilities

• Document the existing architecture of the case-based disease surveillance system
• Maintain current and develop future-state case-based disease surveillance system architectural diagrams
• Facilitate and collaborate with end-users and technical staff to understand requirements
• Evaluate, design, and implement both the existing and proposed future-state disease surveillance system solutions
• Document all aspects of the system architecture
• Create and manage systems and pipelines for efficient data flow
• Collect, transform, clean, and load data into storage systems or data warehouses
• Optimize data pipelines, infrastructure, and workflows for performance and scalability
• Monitor data pipelines and systems for performance issues, errors, and anomalies
• Implement security measures to protect sensitive information
• Collaborate with data scientists, analysts, and other partners to understand their data needs
• Implement and maintain ETL processes
• Design and manage data storage systems