Responsibilities

• Create and manage the systems and pipelines that enable efficient and reliable flow of data, including ingestion, processing, and storage.  Working with Systems Architect, develop and implement data integration plan.
• Collect data from various sources, transforming and cleaning it to ensure accuracy and consistency. Load data into storage systems or data warehouses.  Connect/configure data visualization software to pull key performance metrics into internal dashboards.
• 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.

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, 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 using R and Shiny Apps is preferred.
• 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). Understanding of no code database and survey software.  Experience utilizing Qualtrics and QuickBase preferred.
• Experience with electronic health records, familiarity with eClinicalWorks and Credible preferred.
• 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.
• Familiarity with project management /collaboration software.
• Proficiency in Microsoft Office and Google Suite.