Seeking a full-time Scientific Data Engineer to join the Institutional Informatics Team, this role will provide technical expertise in supporting scientific data generation and compute systems, implementing automated systems, and enhancing laboratory operations while working in a hybrid environment. Key responsibilities Translate functional specifications and system designs into implementations and enhancements for shared data platforms Develop, test, deploy, and maintain core automated systems and workflows to support genomic data generation and metadata management Resolve technical issues creatively while optimizing system architecture and ensuring high standards for reliability and performance Required qualifications Bachelor's Degree in Computer Science or a related field with a minimum of 5 years of relevant experience in software applications and data systems Experience with various database technologies and data engineering tools such as Airflow and Kafka Proficiency in Python and familiarity with additional programming languages Strong knowledge of software and data engineering fundamentals supporting large-scale production systems Experience collaborating with stakeholders to translate complex requirements into automated systems and technical specifications