Research Data Engineer I
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. With moderate supervision and guidance, supports the implementation and maintenance of analytical and data science-based software and data pipelines, enabling scientific workflows. Provides focused support in enhancing the data collection frameworks that integrate structured and unstructured data from multiple sources and systems to enable the used of data in specific research study teams. Maintains and supports the development of infrastructure systems (e.g., data warehouses, data lakes, etc.), including data access APIs. Receives guidance from and acts in support of a team aimed at providing robust, scalable software solutions to the research enterprise.
Requirements
- Bachelor's degree in Data Science, Biomedical Science, Computer Science, Mathematics, Statistics or similar discipline required.
- 1 year of relevant experience required including experience in technology-intensive environments and programming experience in SQL or equivalent combination of education and experience.
- Programming experience, ideally in Java and Python and/or R
- Experience with Linux environments, Docker, and cloud technologies (e.g. AWS, Microsoft Azure, Google Cloud Platform).
- Familiarity with data analytics and statistical methods
- Expertise of software engineering best practices such as version control and software release management
- Strong analytical and problem-solving skills
- Strong organizational skills
- Ability to work with others in a matrix management environment
- Excellent communication skills for describing progress and challenges to stakeholders
- Attention to detail, patience and a positive, customer-centric attitude
- Strong technical presentation skills
- Demonstrated ability to develop proficiency with unfamiliar toolsets.
Nice To Haves
- Experience with laboratory data management systems (e.g. biospecimen software, electronic laboratory notebooks, LabKey Server, REDCap)
- Familiarity with genomics, metagenomics, flow cytometry or imaging files, metadata, and data standards preferred.
Responsibilities
- Maintains and modifies 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 team members to support the conversion of business and technical requirements into professional software solutions.
- Ensures timely completion of tasks while managing multiple assignments, project timelines and business user expectations.
- Supports the implementation of 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.
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
