Responsibilities

• Create and manage the systems and pipelines that enable efficient and reliable flow of data, including ingestion, processing, and storage.
• Assess existing data pipeline and work with programs to envision and assist in developing an ideal future state.
• Collect data from various sources, validating and transforming to conform with defined rules to ensure accuracy and consistency. Load, import data into surveillance 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 protectsensitive and highly confidential 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.

Qualifications

• Bachelor’s degree in computer science, Information Technology, Data Science, or a related field.
• Minimum 5 years of relevant professional experience 
• Proficiency in common scripting languages and specifications used in data engineering, such as Python, R, SAS and SAS Viya readiness.  Candidate must be able to develop reusable automations for data extract, transform and load, harnessing existing frameworks and industry best practices.
• Knowledge of medical coding concepts like LOINCs, SNOMED and ICD-10
• Familiarity with RedCap data collection and extraction
• Ability to transition data to downstream data systems
• Experience with big data technologies and frameworks.
• Strong understanding of transactional (OLTP) and analytical (OLAP) database concepts and systems, including relational database management systems (MS SQL, MySQL, PostgreSQL).
• 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.
• Experience with infectious disease reporting systems is a plus
• 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.