Research Data Manager

Arizona State University•Tempe, AZ

1d•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 activities. Working with investigators, research teams, internal stakeholders, and external partners, the role helps ensure research data remain reliable, secure, accessible, and reusable throughout the research data lifecycle. The position promotes consistent data management practices, upholds institutional standards, and supports 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, data dictionaries, file organization guidelines, and documentation practices; supporting relational databases and data intake pipelines; and executing data quality, validation, transformation, and quality assurance processes. The position also implements data management and sharing plans to promote scientific reproducibility, data stewardship, interoperability, and responsible research data management. The Research Data Manager 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. The role supports PostgreSQL databases, LIMS connections, APIs, data discovery and sharing resources, and coordination of data sharing across research teams. This is a full-time, grant-funded position based on the Tempe campus. The position does not require driving.

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 providing comparable knowledge, skills, and abilities.
Ability to own complex issues and develop scalable solutions and work products, and to plan and lead design, building, and maintenance of platforms and enterprise solutions across IT systems.

Nice To Haves

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 working in academic research environments on projects focused on evolutionary biology, genetics/genomics, biological aging, or organismal/primate biology.
Practical experience with relational database management systems, schema building, maintenance, and querying, particularly PostgreSQL or SQL.
Experience integrating or connecting LIMS, biorepository tracking, or sample inventories with central database infrastructure.
Strong cross-functional communication skills to translate needs between database engineers, principal investigators, and domain scientists.
Experience assisting with automated data intake pipelines, scientific scripting, and APIs.
Demonstrated experience developing data validation, QC/QA procedures, and metadata auditing for complex incoming datasets.

Responsibilities

Integrate large, multi-domain 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, maintain, and assist with continued development of PostgreSQL-based relational databases.
Connect laboratory information management systems (LIMS) and downstream sample tracking to the central biorepository database.
Perform data transformations, data wrangling, and SQL queries to bridge analytical tools and database architecture.
Support maintenance, operation, and administration of APIs in collaboration with other data managers and data scientists.
Collaborate on developing the data discovery and data sharing portal, manage curated metadata releases, and compile relational database content for internal research group usability.
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 compliance with sponsor requirements, data-sharing expectations, institutional standards, and applicable regulatory frameworks.