Rutgers-The State University - New Brunswick, NJ
posted 3 months ago
Rutgers, The State University of New Jersey, is seeking a Data Engineer (Biomedical & Clinical Informatics) for the Office of Advanced Research Computing (OARC). This position is integral to supporting the Rutgers University biomedical research community and other research disciplines in their computing and data-related research. The successful candidate will collaborate with research scientists and biomedical informatics specialists to manage and analyze data generated in molecular and cellular biology, genomics, and biomedicine. This will involve utilizing existing data science and machine learning tools, as well as engineering new toolsets that include models, algorithms, and software developed in-house. The Data Engineer will report to the Director of Research Support under the Associate Vice President for Advanced Research Computing. A significant aspect of this role includes engaging in outreach across Rutgers campuses to identify potential new users of research computing and data resources. The incumbent will work closely with faculty, post-doctoral associates, students, and research staff to understand their research needs, allowing for the customization of workflows, training, and support. There is also an opportunity to grow a biomedical and clinical informatics team based on the demand for these services. Key responsibilities include participating in the development of new biomedical and clinical informatics research and support models, potentially leading to the creation of a core facility or center of excellence. The Data Engineer will develop and maintain data pipelines to facilitate the smooth flow and collection of clinical research data, integrating various sources for comprehensive analysis. They will utilize expertise in data wrangling techniques to clean, transform, and prepare raw data for analysis, ensuring data quality and consistency. Additionally, the role involves providing education, outreach, and training to the university community, optimizing data systems for performance, and collaborating closely with Enterprise Infrastructure teams to align data engineering efforts with broader infrastructure strategies.