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 epidemiologists, 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.

Qualifications

• 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 and analysis, such as Python, R, Java, Scala, or SQL is required. Experience using Python is preferred. Candidate should be able to implement data automations within existing frameworks as opposed to writing one off scripts.
• Experience with data visualization tools is required, proficiency in using, building, and coding in Tableau and ArcGIS is preferred.  Ability to train others in this area.
• 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.
• Familiarity with data equity principles and standards.
• Strong technical documentation skills including building data dictionaries and code books.
• Knowledge/familiarity with sensitive data.
• Knowledge/ability to complete business process analysis, requirements documentation and data flow mapping.
• Must be able to drive projects from concept to completion utilizing critical thinking and change management skills.  Ability to work independently with minimal oversight.