Research Data Engineer II

Location: City of Rochester

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.
** Job Location (Full Address):
** 265 Crittenden Blvd, Rochester, New York, United States of America, 14642
** Opening:
** Worker Subtype:

Regular Time Type:

Full time Scheduled Weekly

Hours:

40

Department:400990 Clin & Trans Science Institute

Work Shift:

UR - Day (United States of America)
Range:

UR URG 113

Compensation Range:$77,216.00 - $
* The referenced pay range represents the minimum and maximum compensation for this job. Individual annual salaries/hourly rates will be set within the job's compensation range, and will be determined by considering factors including, but not limited to, market data, education, experience, qualifications, expertise of the individual, and internal equity considerations.
*** Responsibilities:
** With general supervision and guidance, participates in the design, implementation, and maintenance of informatics tools and solutions to support and accelerate clinical research. Primarily focuses on developing and supporting the data quality assurance and quality control applications, processes, and protocols of the URMC OMOP database and its de-identified version. The role involves leveraging advanced analytics by adopting, deploying, and improving AI/ML models (including LLMs) to enrich OMOP clinical data and enhance its research readiness.

Develop, evaluate and customize open-source tools to support and promote the use of OMOP database for observational healthcare studies. Works in partnership with CTSI Informatics team members and the Information System Division (ISD) at URMC to provide robust, scalable informatics solutions to the research enterprise.
** ESSENTIAL FUNCTIONS
*** Builds, maintains, and evolves data quality evaluation standards, processes, and workflows to monitor and report data accuracy, consistency, and plausibility.  Determines required changes to the Extract, Transform and Load (ETL) pipelines for improved data quality.
* Works with research team members to convert business and technical requirements into professional software solutions. Ensures timely completion of tasks while managing multiple assignments, project timelines, and business user expectations.
* Designs and implements custom, research project-specific data workflow solutions for data collection, management, reporting and analytics. Contributes to the scientific research.
* Participates in specification, implementation and execution of testing procedures to ensure quality of deliverables, system and data workflow reliability.
* Adheres to defined application development life-cycle practices, including but not limited to, requirements gathering, writing test plans, source code management, peer code review, and quality assurance through unit/system/user acceptance testing.
* Produces and maintains comprehensive technical documentation for all systems under the Engineer’s responsibilities.
* Keeps abreast of current application developments through continuing education, professional reading, online forums, conferences, workshops, and professional groups.
* Other duties as assigned
** MINIMUM EDUCATION & EXPERIENCE
*** Bachelor’s degree in Data Science, Biomedical Science, Computer Science, Mathematics, Statistics, or similar discipline required
* 2 years of experience in technology and data intensive roles and environments, or equivalent combination of education and experience required
* Programming experience in SQL and at least one other applicable language (Java, Python, C, and/or R) required.
* Experience implementing and supporting analytical tools in a scientific research or clinical context (e.g. OHDSI HADES) preferred
* Experience with OMOP common data model preferred
* Familiarity with medical vocabularies (e.g., ICD-10-CM, CPT4, LOINC, RxNorm, SNOMED) and reporting clinical data from Epic databases (e.g., Clarity, Caboodle)…