Research Data Engineer II — Medical Research Data Systems

University of Rochester; United States; On-site; USD 78,000 - 116,000; Full time

Job summary

University of Rochester seeks a data-focused professional to design and maintain research databases and big data repositories for medical research. You will collaborate with investigators and biostatisticians, implement efficient data architectures, and support reporting and analytics for large grants.

The role requires SQL and at least one other language, experience with Linux and SAS, and a background in data science or related field. Strong communication and documentation skills are essential.

Qualifications

• Bachelor's degree in data science, biomedical science, computer science, mathematics or statistics plus 2 years in tech roles.
• Master's degree preferred.
• Programming experience in SQL and one other language (Java, Python or R) required.
• Experience with Linux, container and cloud technologies preferred.

Responsibilities

• Design, implement, and maintain research database infrastructure for data collection and analytics.
• Develop and support large, complex medical research data sources and architecture.
• Collaborate with investigators, staff, and biostatisticians to gather data requirements.
• Program and test applications, manage code quality, and perform unit tests.
• Produce and maintain technical documentation and stay current with best practices.

Skills

SQL

Python

Java

R

Statistics

Education

Bachelor's degree in data science / related field

Master's degree preferred

Equivalent education and experience

Tools

Git

SAS

Linux

Docker

HPC

Job description

University of Rochester seeks a data-focused professional to design and maintain research databases and big data repositories for medical research. You will collaborate with investigators and biostatisticians, implement efficient data architectures, and support reporting and analytics for large grants.

The role requires SQL and at least one other language, experience with Linux and SAS, and a background in data science or related field. Strong communication and documentation skills are essential.