R&D Data Stewardship Lead

Almirall; Sant Feliu de Llobregat; Presencial; EUR 90 000 - 130 000; Tempo integral

Resumo da oferta

Almirall is seeking a Data Stewardship Manager to lead the Molecules data strategy within R&D, driving digital solutions, data governance, and analytics to accelerate drug development. You will collaborate with scientists, IT, and data teams to translate scientific needs into scalable data architectures.

The role emphasizes governance, data standards, and enabling AI-enabled capabilities while ensuring data integrity and regulatory alignment across analytical workflows.

Qualificações

• Bachelor’s or Master’s degree in Pharmaceutical Sciences, Biochemistry, Data Science, or a related discipline is desirable.
• Experience in pharmaceutical or Biotech R&D, analytical development, laboratory informatics, or scientific data management ecosystems is a must.
• Working knowledge in programming languages (e.g. Python, SQL etc.) is desirable.
• Ability to manipulate, analyse, and automate scientific data workflows is a must.
• Strong understanding of analytical laboratory workflows and associated scientific data.
• Practical knowledge of data governance, including metadata, data quality, data lineage, data ownership, taxonomies, and data lifecycle management.
• Experience translating scientific requirements into structured data and technology requirements.
• Strong communication, problem-solving, facilitation, and stakeholder-management skills, with the ability to explain complex scientific and data concepts to laboratory, technical and senior leadership audiences.

Responsabilidades

• Represent the Molecules organisation in shaping and implementing the broader R&D digital and data roadmap, ensuring its scientific needs, priorities, and workflows are incorporated into scalable digital solutions.
• Lead scientific workflow and data discovery sessions with laboratory teams, mapping experimental processes, data flows, calculations, decision points and exceptions to identify opportunities for standardization, automation and reuse.
• Drive adoption of agreed data standards and digital workflows by developing guidance, training users, supporting onboarding and acting as a trusted partner to laboratory teams during changes in tools and ways of working.
• Partner with IT/Digital, Data Sciences, and laboratory teams to translate the R&D digitalization roadmap into harmonised data structures and practices across analytical techniques, therapeutic modalities, and laboratories.
• Establish and coordinate the stewardship and governance of analytical and drug development data generated by internal laboratories and external partners, providing the trusted data foundation required to deliver the R&D digitalization roadmap.
• Define and maintain data standards, metadata, data dictionaries, taxonomies, controlled vocabularies, critical data elements, and FAIR principles.
• Translate scientific needs into data and system requirements for ELN, LIMS, repositories, and other digital solutions.
• Ensure data practices remain lean and efficient in non-GxP environments while meeting applicable data integrity, quality, regulatory, and GxP requirements where needed.
• Enable automation, advanced analytics, and AI through fit-for-purpose scientific data.
• Coordinate effectively with IT/Digital, Data Science, Quality, Regulatory, and other R&D stakeholders.

Conhecimentos

Python

SQL

Communication

Problem-solving

Stakeholder management

Analytical thinking

English fluency

Formação académica

Bachelor’s or Master’s in Pharmaceutical Sciences

Biochemistry

Data Science

Ferramentas

ELN

LIMS

CDS

SDMS

scientific data repositories

Descrição da oferta de emprego

Almirall is seeking a Data Stewardship Manager to lead the Molecules data strategy within R&D, driving digital solutions, data governance, and analytics to accelerate drug development. You will collaborate with scientists, IT, and data teams to translate scientific needs into scalable data architectures.

The role emphasizes governance, data standards, and enabling AI-enabled capabilities while ensuring data integrity and regulatory alignment across analytical workflows.