Research Data Engineer II, CHeT Analytics

University of Rochester•City of Rochester, NY

11d

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. GENERAL PURPOSE 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.

Requirements

Bachelor's degree in Data Science, Biomedical Science, Computer Science, Mathematics, Statistics or similar discipline and 2 years of experience in technology and data intensive roles and environments required
Or equivalent combination of education and experience
Programming experience in Structured Query Language (SQL) and one other applicable language (Java, Python, and/or R) required
Experience with Change Management solutions required
Experience with Version Control solutions (e.g. Git) required
Understanding of data analytics and statistical methods required
Expertise of software engineering best practices such as version control and software release management required
Strong analytical and problem-solving skills required
Strong organizational skills required
Ability to work with others in a matrix management environment required
Excellent communication skills for describing progress and challenges to stakeholders required
Attention to detail, patience and a positive, customer-centric attitude required
Strong technical presentation skills required
Familiarity with file formats, metadata, and data exchange and storage standards applicable in management of scientific and clinical research required

Nice To Haves

Experience implementing and supporting data management systems in a scientific, research context (e.g. biospecimen software, electronic laboratory notebooks, REDCap) preferred
Experience with Linux, container and cloud technologies (e.g. HPC, IaaS and PaaS) preferred
Demonstrated ability to develop proficiency with unfamiliar toolsets preferred

Responsibilities

Builds, maintains and evolves general Extract, Transform and Load (ETL) data pipelines and overall data architecture to accommodate a growing amount of data from a variety of large research data sources.
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.
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.
Participates in specification, implementation and execution of testing procedures to ensure quality of deliverables, system and data workflow reliability.
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.