Data Engineer

CDC Foundation•Oklahoma City, OK

2h•Remote

About The Position

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. 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 the Chickasaw Nation Department of Health (CNDH), Division of Public Health, the Data Engineer will collaboratively plan and develop solutions for interoperable data generation, storage, processing, and analysis across data systems relevant to the tribal public health agency. The Data Engineer will collaborate with the CNDH Division of Public Health team and 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, all while providing training and mentorship to the Division of Public Health staff for capacity development and system sustainability. The Data Engineer will be hired by the CDC Foundation and assigned to the CNDH Division of Public Health. This position is eligible for a fully remote work arrangement for U.S. based candidates.

Requirements

Bachelor's degree in Computer Science, Information Technology, Data Science, or a related field.
Minimum 5 years of relevant professional experience
Proficiency in programming languages commonly used in data engineering, such as R, 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).
Expertise in data modeling, ETL (Extract, Transform, Load) processes, and data integration techniques.
Knowledge of data warehousing concepts and tools.
Experience regarding engineering best practices such as source control, automated testing, continuous integration and deployment, and peer review.
Experience with cloud computing platforms.
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.
Proficiency in Microsoft Office.

Nice To Haves

Experience with large/national datasets and Epic Health Record systems is preferred.
Experience with data visualization tool Power BI.
Experience working with tribal nations and tribal data sovereignty is preferred.
Experience working in a virtual environment with remote partners and teams.

Responsibilities

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.
Knowledge 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.
Communicate effectively with partners at all levels of the organization to gather requirements, provide updates, and present findings.
Up to 10% domestic travel may be required.