Research Data Engineer II

University of Rochester•City of Rochester, NY

About The Position

As a community, the University of Rochester is defined by a deep commitment to Meliora - Ever Better. Embedded in that ideal are the values we share: equity, leadership, integrity, openness, respect, and accountability. Together, we will set the highest standards for how we treat each other to ensure our community is welcoming to all and is a place where all can thrive. Located in western New York, Rochester is our namesake and our home. One of the world’s leading research universities, Rochester has a long tradition of breaking boundaries—always pushing and questioning, learning and unlearning. We transform ideas into enterprises that create value and make the world ever better. If you’re looking for a career in higher education or health care, the University of Rochester may offer the perfect opportunity for your background and goals. At the University of Rochester, we are committed to fostering, cultivating, and preserving an inclusive and welcoming culture and are united by a strong commitment to be ever better—Meliora. It is an ideal that informs our shared mission to ensure all members of our community feel safe, respected, included, and valued.

Requirements

BS in Biomedical Science, Computer Science, or Data Science at least 2 years of experience in data-intensive roles or MS degree in equivalent field

Nice To Haves

Data engineering, programming, scientific data management, statistical methods for scientific and clinical research
Proficiency in coding ability (Python, R) for data processing and analysis
Advanced statistical analysis
Strong organizational and problem solving skills.

Responsibilities

Participates in the design, implementation and maintenance of analytical and data science-based software and data pipelines to support scientific workflows.
Focuses on developing and supporting data collection frameworks that integrate structured and unstructured data from multiple sources and systems to support specific research study teams.
Supports the development and maintenance of infrastructure systems (e.g., data warehouses, data lakes), including data access Application Programming Interface(s) (APIs).
Works in partnership with team members to provide robust, scalable software solutions to the research enterprise.
Apply statistical tools to biomedical datasets.
Develop custom scripts in R and Python to support translational research.
Maintain metadata standards and ensure compliance with FAIR principles for scientific data.
Deploy and manage computational jobs, optimizing workflows for large-scale bioinformatics and statistical analyses.
Ensure efficient resource allocation for complex modeling tasks.
Produce detailed technical documentation for workflows and data analysis for reproducible research.
Mentor team members on best practices and version control.
Active involvement in manuscript and grant writing under the guidance of the PI.
Work closely with research teams to translate biological questions into computational solutions.
Present technical progress and challenges clearly to technical and non-technical stakeholders.
Other duties as assigned.