The Directorate of Human and Robotic Exploration Programmes (D/HRE) is a programme directorate within the ESA matrix structure. Using a partnership between humans and robots, the Directorate is dedicated to exploring destinations in space where humans are already living and working – or will live and work in the future – for the purpose of scientific research, economic development, international cooperation and public inspiration.

The Lead for Exploration Science Data and Archiving is responsible for the coordination, implementation and oversight of all activities related to the archiving, dissemination, exploitation and re-exploitation of scientific data generated through Human and Robotic Exploration (HRE) activities. Through the implementation of the European Exploration Envelope Programme (E3P), many datasets of various nature are generated from a large portfolio of ground-based, suborbital and low-Earth orbital platforms, complemented by robotic missions to the Moon/Mars orbit and surface. HRE handling of those datasets is also implemented in synergy with the ESA Science (SCI) Directorate.

The Exploration Science Data and Archiving function ensures the preservation, traceability, accessibility, and compliant re-use of HRE scientific, technical, operational and programme data. The function ensures that datasets and associated documentation are delivered, described, validated and ingested into appropriate ESA archives in accordance with the HRE Data Policy, FAIR principles, personal data protection rules, partner agreements, and long-term preservation requirements. Hence this function encompasses sizeable interactions between various scientific and operations communities and acts as the interface between HRE Programme teams, investigators, operations centres, data centres, legal/data-protection experts, industrial contractors, and international partners, while maintaining archive status reporting, risk tracking and continuous improvement of HRE archiving processes

Hierarchical reporting lines will be to the Chief Exploration Scientist (HRE-S), with strong interfacing and collaboration with the Science Archives (SCI-SAA) and the Software and Artificial Intelligence Team (HRE-FI) and activities.

Duties

• Act as the central point of contact for HRE data archiving matters across relevant HRE programme lines, missions, platforms, facilities and utilisation activities.
• Oversee the implementation of the HRE data policy in line with the approved documentation, including rules on data ownership, access rights, exclusive-use periods, dissemination, re-use and long-term preservation.
• Maintain an overview of applicable archiving obligations arising from ESA policies, programme decisions, international agreements, mission-specific arrangements and data management plans.
• Contribute to the harmonisation of archiving practices across HRE activities, including ISS, post-ISS, analogue platforms, commercial platforms, and ground-based research facilities, and Lunar/Martian missions, where applicable.
• Coordinate with HRE programme managers, project scientists, project teams, payload developers, USOCs, operations centres, data centres and external partners to ensure that archiving requirements are understood and implemented.
• Consolidate completion status of all approved and implemented utilisation activities.
• Ensure appropriate dissemination, valorisation, and long-term preservation of experimental datasets.
• Coordinate the archiving tasks managed by the HRE Science Data Centre (SDC) located in Madrid, Spain.
• Coordinate interfacing with and crosslinking of HREDA with other ESA science archives, such as the Planetary Sciences Archive (PSA), Heliophysics, etc.
• Ensure the HREDA supports the dissemination and secure archiving of medically sensitive datasets, including clearance from the ESA Data Protection Officer for all involved entities.
• Organise structured tracking of scientific publications arising from HRE activities to support ESA-wide key performance indicators (KPIs) under the Digital Agenda initiative.
• Manage the curation of the public content of the legacy Erasmus Experiment Archive (EEA) and oversee its progressive ingestion into the HREDA portal.
• Support regular reporting to HRE programmatic boards, as required.

Technical competencies

Behavioural competencies

Result Orientation
Operational Efficiency
Fostering Cooperation
Relationship Management
Continuous Improvement
Forward Thinking

For more information, please refer to ESA Core Behavioural Competencies guidebook

Education and professional experience

A PhD in a relevant domain is required for this post together with four years of relevant professional experience.

Additional requirements

• Strong understanding of scientific data lifecycle management, including metadata standards, data integrity, versioning, and provenance.
• Experience with scientific data archiving systems, digital repositories, and FAIR (Findable, Accessible, Interoperable, Reusable) data principles.
• Familiarity with data governance, particularly in relation to sensitive data (e.g. biomedical data), including GDPR and data protection compliance.
• Understanding of the specific constraints associated with human-subject research data.
• Ability to distinguish between open data, restricted data, confidential data, medically sensitive data, personal data, anonymised data and pseudonymised data.
• Ability to review heterogeneous technical, scientific, operational, legal and programme information so as to extract archive-relevant implications.
• Ability to identify what data information is essential for future intelligibility and re-use.
• Proven experience in coordinating multidisciplinary teams and interfacing between scientific, technical and policy stakeholders.
• Knowledge of Open Science frameworks and data publication best practices.
• Experience with data infrastructure, including database management systems.
• Understanding of data processing workflows, and experience in defining data models, metadata schemas across heterogeneous datasets.
• Familiarity with data exploitation approaches, including scientific data analysis environments, machine learning readiness and user-oriented data services. Experience with ESA’s data systems or equivalent research agency environments is considered an advantage.