Data Engineer - Alaska

Job Highlights· Location: Remote, must be based in the United States· Salary Range: $115,000-$165,000, plus benefits· Position Type: Grant funded, limited-term opportunity· Position End Date: June 30, 2025

Overview

• 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. Working within the Alaska Division of Public Health, Section of Public Health Nursing, the Data Engineer will play a crucial role in transforming and loading data into the new Electronic Health Record (EHR) system. This position goes beyond mere database merging; it involves creating a unified, patient-centered database to replace the current location-based system and will serve as the foundational EHR. The Data Engineer will handle complex ETL tasks such as data mapping to establish relationships between disparate data sets, data transformation to standardize and convert data formats to the new SQL database structure, data cleansing to ensure data integrity, and data preparation to import efficiently with minimal downtime and service disruption. This role requires collaboration with data content experts, analysts, end-users, IT staff and other organizational personnel to design and implement solutions that meet the needs of the Division.
• The Data Engineer will be hired by the CDC Foundation and assigned to the Alaska Division of Public Health, Section of Public Health Nursing. This position is eligible for a fully remote work arrangement for U.S. based candidates

Responsibilities

• Establish relationships between disparate databases to ensure accurate and effective data consolidation.
• 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, ensuring data handling practices comply with relevant regulations and standards, particularly 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 …