Data Engineer

The Data Engineer will play a crucial role in advancing the CDC Foundation's mission by designing, building, and maintaining data infrastructure for a public health organization and working within the Great Lakes Inter-Tribal Epidemiology Center. The Data Engineer will deliver the architecture needed for data linkages, storage, processing, and analysis. The Data Engineer will collaborate with data content experts, analysts, data scientists, data modelers, warehouse architects, IT staff, and other organization staff to design and implement proposed solutions and architectures that meet the needs of the public health agency. The Data Engineer will also work with current staff to increase their knowledge while allowing for the sustainability of the project to the Tribes as more data sets are added. The Data Engineer will be hired by the CDC Foundation aligned to the Workforce Acceleration Initiative (WAI) and assigned to the Great Lakes Inter-Tribal Epidemiology Center, which is a program of the Great Lakes Inter-Tribal Council. This position is eligible for a fully remote work arrangement for U.S. based candidates.

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 to handle growing data volumes associated with public health initiatives.


Monitor data pipelines and systems for performance issues, errors, and anomalies, and implement solutions to address them.


Implement security measures to protect sensitive public health information, complying with relevant regulations (e.g., HIPAA).


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.


Provide technical guidance to Tribes as requested.


Communicate effectively with partners at all levels of the organization to gather requirements, provide updates, and present findings.

Bachelor's degree in Computer Science, Information Technology, Data Science, or a related field.


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 big data technologies and frameworks like Hadoop, Spark, Kafka, and Flink.


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 based computing and data storage solutions (e.g. AWS S3, Azure).


Expertise in data modeling, ETL (Extract, Transform, Load) processes, and data integration techniques.


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.


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.


Knowledge of data security best practices specific to healthcare data (e.g., HIPAA compliance).


Experience with DevOps principles and tools for automating data pipelines and infrastructure deployments