Remote Data Engineer

Summary

Join the CDC Foundation as a Data Engineer to design, build, and maintain data infrastructure for a public health organization. This role will play a crucial part in advancing the CDC Foundation's mission by providing technical guidance and collaborating with cross-functional teams.

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
• 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 and/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