Data Stewardship Manager

As a Data Stewardship Manager you will join the Analytical & Formulation Sciences team within the Molecules organisation in Almirall R&D. You will drive and advance the organisation's digital and data strategy, by representing Molecules in shaping the Almirall R&D digital and data roadmap, partnering closely with scientists, laboratory teams, Data Science, and IT/Digital to translate scientific needs into aligned, scalable digital solutions. The role will build the trusted scientific data foundation needed to accelerate R&D, strengthen decision-making, and unlock future digital and AI-enabled capabilities.

Responsibilities

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

Requirements

Experience in pharmaceutical or Biotech R&D, analytical development, laboratory informatics, or scientific data management ecosystems; Ability to manipulate, analyse, and automate scientific data workflows; 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; Fluency in spoken and written English

Nice to have

Bachelor's or Master's degree in Pharmaceutical Sciences, Biochemistry, Data Science, or a related discipline; Working knowledge in programming languages (e.g. Python, SQL etc.); Experience with laboratory systems such as ELN, LIMS, CDS, SDMS, or scientific data repositories; Familiarity with analytical techniques and their associated data; Experience with data harmonisation, migration, integration, or laboratory-system implementation; Understanding of FAIR data principles, pharmaceutical data integrity, and GxP expectations; Exposure to automation, advanced analytics, AI, and machine learning in scientific environments; Scientific mindset combined with a pragmatic, collaborative, innovative, and change-oriented approach; Other languages are a plus