Research Data Manager

Arizona State University•Tempe, AZ

2d•$85,700 - $95,000•Onsite

About The Position

The Research Data Manager supports ASU’s Knowledge Enterprise by designing, implementing, coordinating, and stewarding research data management activities for research projects, initiatives, and operational work. In collaboration with investigators, research teams, internal stakeholders, and external partners, the role helps ensure research data remain reliable, secure, accessible, and reusable throughout the data lifecycle. The position promotes consistent data management practices, institutional standards, and compliance with sponsor requirements, data-sharing expectations, and applicable regulatory frameworks. The role develops, implements, maintains, and improves research data systems, workflows, standards, and documentation for complex, multidisciplinary research initiatives. Work includes coordinating data collection and integration, establishing metadata standards and data documentation practices, supporting relational databases and data intake pipelines, and carrying out data quality, validation, transformation, and quality assurance processes. The Research Data Manager also implements data management and sharing plans to promote reproducibility, stewardship, interoperability, and responsible research data management. The position integrates large, multi-domain datasets from free-ranging nonhuman primates, including multi-omic data, immune phenotyping, social-network phenotypes, longitudinal physiological measures, survival, and reproductive outcomes. It supports PostgreSQL databases, LIMS and biorepository connections, APIs, and a data discovery and sharing portal. The role serves as the primary point of contact for data sharing across project cores, sub-projects, and collaborative research teams.

Requirements

Bachelor’s degree and seven years of experience appropriate to the area of assignment or field, or an equivalent combination of experience and/or training demonstrating comparable knowledge, skills, and abilities.
Master’s degree plus at least three years of relevant professional experience, or a PhD, as stated among the desired qualifications.
Experience with relational database management systems, schema building, maintenance, and querying, particularly PostgreSQL or SQL.
Strong cross-functional communication skills to translate needs between database engineers, principal investigators, and domain scientists.
Experience developing data validation and QC/QA procedures and conducting metadata auditing for complex incoming datasets.

Nice To Haves

A master’s degree plus three or more years of relevant professional experience, or a PhD in computational biology, bioinformatics, genetics, genomics, evolutionary biology, quantitative biology, anthropology, aging biology, or a closely related quantitative life sciences or data discipline.
Experience in academic research environments on projects focused on evolutionary biology, genetics/genomics, biological aging, or organismal/primate biology.
Experience integrating or connecting LIMS, biorepository tracking, or sample inventories with central database infrastructure.
Experience assisting with automated data intake pipelines, scientific scripting, and APIs.

Responsibilities

Integrate multi-domain, large-scale datasets from free-ranging nonhuman primates, including single-cell and bulk-tissue multi-omic data, immune phenotyping, social-network phenotypes, longitudinal physiological measures, survival, and reproductive outcomes.
Assist with developing and refining data intake pipelines for complex incoming datasets.
Administer and maintain PostgreSQL-based relational databases and assist with their continued development.
Connect laboratory information management systems (LIMS) and downstream sample tracking to the central biorepository database.
Perform data transformations, data wrangling, and SQL queries to connect analytical tools with database architecture.
Support the maintenance, operation, and administration of APIs in collaboration with other data managers and data scientists.
Collaborate on developing the data discovery and sharing portal, manage curated metadata releases, and compile relational database content for internal research-group use.
Serve as the primary point of contact for data sharing across project cores, sub-projects, and collaborative research teams.
Implement data validation, auditing, standardization, and quality assurance procedures to maintain dataset integrity.
Monitor the operational health of supported data systems and participate in cross-functional technical meetings and project coordination activities.
Develop, implement, maintain, and improve research data systems, workflows, standards, and documentation.
Coordinate data collection and integration across and within research teams; establish metadata standards, data dictionaries, file organization guidelines, and documentation practices.
Support relational databases and data intake pipelines; execute data quality, validation, transformation, and quality assurance processes.
Implement data management and sharing plans to promote reproducibility, data stewardship, interoperability, and responsible research data management.