Data Engineer

CDC Foundation

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 Illinois Department of Public Health, to build, optimize, and manage cloud-based data pipelines and ETL processes on the Snowflake platform. This role will focus on implementing high-performance data systems, ensuring the reliability and scalability of our data infrastructure, and enabling robust analytics and insights for the organization. The ideal candidate will have hands-on experience with Snowflake, cloud environments, and data engineering best practices. The Data Engineer will be hired by the CDC Foundation and assigned to the Illinois Department 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 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.
High level of proficiency in Snowflake, including advanced features like Time Travel, Zero-Copy Cloning, and data sharing is required. 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. Familiarity with data lake and lakehouse architectures.
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

Develop a detailed plan for database migration, ETL processes, and data processing applications.
Design, build, and manage ETL/ELT processes and data pipelines on the Snowflake platform, ensuring the movement of large datasets between various data sources. Develop efficient, scalable data architectures and implement Snowflake best practices, including partitioning, clustering, and query optimization for performance and cost. Collaborate with data scientists, analysts, and Local health departments to integrate diverse data sources into Snowflake, ensuring data is available for analytics and reporting.
Monitor data pipelines and systems for performance issues, costs, errors and anomalies, and implement solutions to address them.
Collaborate with the IT Security Team to conduct security and access testing. Implement security measures to protect sensitive information.
Collaborate with cross-functional teams to understand data requirements and design scalable solutions that meet business needs. Collaborate with Systems Architect on overall system health, focusing on data aspects and data warehouse. Collaborate with Systems Architect on infrastructure assessment, focusing on data aspects.
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. Create and maintain clear documentation for ETL processes, data pipelines, data models, and infrastructure setups. Develop training materials and conduct online sessions on accessing and utilizing shared data.
Communicate effectively with partners at all levels of the organization to gather requirements, provide updates, and present findings.
Create a data governance framework for secure and compliant data sharing.
Establish successful connection migration plan for ETL processes and APIs between migrated applications and databases.
Implement automated processes for data extraction from source systems and loading into the data warehouse.
Migrate ETL processes and APIs to the cloud environment.
Up to 10% domestic travel may be required.