Data Repository Lead

Job Purpose The Data Repository Lead will lead the development, launch, management and expansion of KAUST’s institutional data repository and its associated services, a core component of the University’s research data management ecosystem. The role ensures trustworthy stewardship and discoverability of research data by implementing workflows for deposit, curation, metadata quality, persistent identifiers (e.g., DOIs for datasets, ORCID iDs for contributors), access control (including internal research data asset cataloging and embargoes), and long-term preservation.

The Lead consults widely with researchers across the university to identify and prioritize their needs and partners with IT, Core Labs, Research Compliance, and other university stakeholders to integrate systems and automate pipelines that support funder / publisher compliance, ethical and legal requirements, and the FAIR principles. Success will be demonstrated through service reliability, growth in high-quality deposits and demonstrable reuse, researcher satisfaction, and alignment with KAUST’s RDM policy, international standards, and community best practices.

Major Accountabilities

Work closely with the library manager to develop direction for KAUST’s institutional data repository, in consultation with KAUST researchers and other university stakeholders, and in alignment with KAUST strategy and policies.

Develop and implement guidelines and procedures for internal research data asset cataloging, public release of eligible datasets, metadata review, removal, retention, and dataset versioning.

Work with external vendors and internal partners to evaluate and implement suitable systems.

Connect the data repository with single sign on, storage platforms, instruments / Core Labs data pipelines, data management planning tools, publications repositories and current research information systems, persistent identifier services (DataCite and ORCID), and other relevant system APIs for metadata synchronization and reporting.

Regularly consult with researchers to identify their needs and tailor services to their requirements.

Deliver training and support for researchers and coordinate improved data management planning and the application of the FAIR principles with research data stewards and champions to increase the long-term value derived from research data assets.

Ensure repository services comply with KAUST policies, funder / publisher requirements, and legal / ethical standards.

Promote discovery and interoperability by establishing robust links between data, related publications, and research software / code.

Monitor service health (uptime / fixity, number and quality of deposits, curation process times, storage use) and impact (downloads / citations, user satisfaction) through dashboards and regular reports.

Competencies Required :

Demonstrated expertise with at least one major institutional data repository or research data platform (Invenio, Figshare, Dataverse or comparable).

Demonstrated proficiency and familiarity with current issues in research data management, including FAIR principles, metadata standards, persistent identifiers (DOIs, ORCID iDs), longterm preservation, and compliance with legal / ethical / publisher / funder requirements.

Experience developing and implementing workflows for data deposit, curation, metadata quality control, versioning, access control, and embargo management.

Strong project management skills with the ability to manage multiple projects concurrently, set and meet deadlines, and adapt to evolving priorities and technologies.

Demonstrated ability to deliver training, guidance, and outreach, and to promote good research data management practices among faculty, researchers, students, and staff.

Excellent communication and collaboration skills, with experience working effectively across diverse academic populations and with external vendors / partners.

A strong user focus and service orientation, with excellent analytical, interpersonal, and problem-solving skills, and the ability to embrace innovation and continuous improvement.

Preferred :

Experience integrating data repository platforms with research management systems, lab data pipelines, researcher workflows and storage platforms.

Familiarity with international best practices and emerging trends in research reproducibility, intellectual property laws (including data licensing), and academic research evaluation practices.

Familiarity with APIs, scripting, or automation for metadata synchronization, reporting, and system interoperability.

Experience monitoring service performance through dashboards and analytics.

Qualifications

Required : Master’s degree in library science, information science, data science, a data intensive scientific discipline relevant to research done at KAUST, or equivalent education and experience.

Preferred : PhD or equivalent advanced degree in a relevant field.

Experience

Minimum 5-7 years of experience in research data management, research data repositories, or related research data stewardship or data management planning work.

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