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 Southern Plains Tribal Health Board and the Oklahoma Area Tribal Epidemiology Center, develop and maintain secure data management systems infrastructure, to allowing for data transfer from various sources and warehouses (including Tribal, State, and Federal systems). Collaborate with IT, WAI lead, cybersecurity and governance personnel in development and implementation of standards, interoperability, and other data modernization infrastructure for integrity and compliance. The Data Engineer will be hired by the CDC Foundation and assigned to the Tribal Epidemiology Center. 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 Python, Java, Scala, or SQL. Candidate should be able to implement data automations within existing frameworks as opposed to writing one off scripts.
Familiarity with public health analytic software, such as Tableau and R.
Experience with electronic medical records (EMR) system implementations (e.g. EPIC).
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 computing platforms.
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.

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.
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.
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.