Overview

• The Data Engineer will play a crucial role in advancing the designing, building, and maintaining data infrastructure. This role is aligned to the Workforce Acceleration Initiative (WAI). WAI is a federally funded CDC Foundation program with the goal of helping the nation’s public health agencies by providing them with the technology and data experts they need to accelerate their information system improvements. Working within South Dakota Department of Health’s (SD-DOH) Epidemiology, Surveillance and Informatics Center (ESIC), the Data Engineer will play a pivotal role in documenting and maintaining the case-based disease surveillance system architecture required for data generation, storage, processing, and analysis. This position is eligible for a fully remote work arrangement for U.S. based candidates.  

Responsibilities

• Document the existing architecture of the case-based disease surveillance system, including system interactions and data generation, storage, processing, and analysis.
• Maintain current and develop the future-state case-based disease surveillance system architectural diagrams to ensure the system continues to be robust, scalable, and aligned with the SD-DOH’s public health goals.
• Facilitate and collaborate with end-users and technical staff to understand requirements and deliver effective surveillance system solutions.
• Evaluate, design, and implement both the existing and proposed future-state disease surveillance system solutions. Ensure that the solutions meet the needs of all stakeholders within SD-DOH, including being adaptable to evolving challenges. This includes conducting an environmental scan of system requirements completed by other jurisdictions.
• Document all aspects of the system architecture, including design decisions, data flow processes, and system requirements. Maintain clear and comprehensive records to support ongoing system maintenance and future upgrades.
• A work product for this position includes creating a final requirements document with all necessary technical specifications for a future-state case-based surveillance system listed clearly and concisely.
• Create and manage the systems and pipelines that enable efficient and reliable flow of data, including ingestion, processing, and storage.
• Collect data from various sources, transforming and cleaning it to ensure accuracy and consistency. 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, and implement solutions to address them.
• Implement security measures to protect sensitive information.
• Collaborate with data scientists, analysts, and other partners to understand their data needs and requirements, and to ensure that the data infrastructure supports the organization’s goals and objectives.
• Collaborate with cross-functional teams to understand data requirements and design scalable solutions that meet business needs.
• Implement and maintain ETL processes to ensure the accuracy, completeness, and consistency of data.
• Design and manage data storage systems, including relational databases, NoSQL databases, and data warehouses.
• Knowledgeable about industry trends, best practices, and emerging technologies in data engineering, and incorporating the trends into the organization’s data infrastructure.
• Provide technical guidance to other staff.
• Work closely with a multidisciplinary team, including data content experts, analysts, data scientists, epidemiologists, IT staff, and other organizational personnel.
• Communicate effectively with partners at all levels of the organization to gather requirements, provide updates, and present findings.

Qualifications

• Bachelor’s degree in Computer Science, Information Technology, Data Science, or a related field.
• 5 years of experience with project oversight, including communications to end-users and technical staff
• Proficiency in programming languages commonly used in data engineering, such as Python, Java, Scala, or SQL. Candidate should be able to implement data automations within existing frameworks as opposed to writing one off scripts.
• Experience with Microsoft Azure cloud technologies and frameworks or similar (AWS).
• Strong understanding of database systems, including relational databases (e.g., MySQL, PostgreSQL) and NoSQL databases (e.g., MongoDB, Cassandra).
• 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, including the ability to convey technical concepts to non-technical partners effectively.
• 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; and the ability to develop productive working relationships with colleagues and partners.
• Experience working in a virtual environment with remote partners and teams
• Proficiency in Microsoft Office.