Senior Specialist, R&D Data Transformation

Posted date Jun. 11, 2026
Contract type Full time
Job ID R\-254125

Why choose AstraZeneca Spain?
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AstraZeneca Spain is a rising force in our global business. With headquarters in Madrid and our global hub in Barcelona, we’ve become an important international centre of excellence in the fight against critical disease. Boasting vibrant universities and business schools, the Barcelona ecosystem is a place where scientists can thrive. We attract a diverse workforce from across the globe, shining a beacon for innovation in a country that’s committed to clinical development.

We invite you to bring your talents to Barcelona where our respiratory medicine R\&D and Global Marketing centre offers opportunities in R\&D, IT, Commercial and HR. Or join us in Madrid and shape our growth in our BUs (Respiratory, Oncology \& CVRM ), and a range of Corporate functions. Additionally, you can find sales roles throughout the country. Together, we’re contributing to a world\-leading pipeline of therapeutics and delivering life\-changing medicines to patients.

Who do we look for?
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Calling all tech innovators, ownership takers, challenge seekers and proactive collaborators. At AstraZeneca Spain, breakthroughs born in the lab become transformative medicine for the world's most complex diseases. Alongside technical expertise, colleagues have the resilience, energy and collaborative mindset to change lanes, work with different teams and start projects from scratch.

Here, diverse minds and bold disruptors can meaningfully impact the future of healthcare using cutting\-edge technology. Whether you join us in Madrid or Barcelona, you can make a tangible impact within a global biopharmaceutical company that invests in your future. Join a talented global team that's powering AstraZeneca to better serve patients every day.

Success Profile
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Ready to make an impact in your career? If you're passionate, growth\-orientated and a true team player, we'll help you succeed. Here are some of the skills and capabilities we look for.

Diverse collaborators

This is a speak\-up culture that values collaboration. You’ll proactively bring your unique perspectives, experiences and skills to the table and seek the same from others. With our international team composition and the need for fast\-paced collaboration, you’ll always be building new connections with colleagues.

Cutting\-edge innovators

When you join us, you’ll be part of a team that embraces digital technology and data to transform the way we work and the work we do. Every day, you’ll help make history, empowered to ignite your creativity and build something enduring.

Resilient trailblazers

Here, the answers aren’t always available. So, you’ll need to bring a fearless, self\-starter mindset to navigate uncharted territories. You’ll harness your ceaseless energy to discover and make the necessary connections with colleagues to shape the future and achieve maximum impact.

Agile movers

Seize ownership and excel with autonomy to enjoy the constant rush of ground\-breaking discovery. Your ability to anticipate sudden shifts and adapt swiftly will prove critical as you make your mark in an environment that rewards initiative and resilience.

Responsibilities
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Job ID R\-254125 Date posted 06/11/2026
Introduction to the Role

The Manager, R\&D Data Transformation coordinates and delivers transformation activities that improve the readiness, interoperability, and reuse of data across AstraZeneca's R\&D data estate. This role brings strong analytical capability, delivery rigour, and growing domain expertise to execute transformation initiatives that ensure R\&D data is AI\-ready and "available by default," directly supporting the AI30 ambition and Ambition 2030\. The Manager delivers within defined workstreams — partnering with R\&D functions, AI for Science Innovation, Enterprise AI Technology, and IT to implement solutions that enable seamless data flow across the R\&D lifecycle.

Scope of Accountability

You will operate as a practitioner within the R\&D Data Transformation team, with accountability across the following areas:

R\&D Data Readiness: Execute transformation activities that bring R\&D data assets to the quality, structure, and completeness standards required to power AI, machine learning, and advanced analytics, delivering defined tasks and workstream components under the guidance of senior team members.

Interoperability and Standards: Support the implementation of enterprise and industry data standards (ontologies, vocabularies, schemas, FAIR principles) within assigned transformation activities, working with domain teams to resolve interoperability issues in practice.

Data Reuse and Discoverability: Develop and maintain cataloguing processes, metadata enrichment activities, and reporting that support findability and reuse of R\&D data assets within assigned domains.

Transformation Delivery: Coordinate and deliver defined transformation activities — applying established methodology and tools, managing task\-level dependencies, and ensuring quality and completeness of outputs.

Process and Tool Development: Develop and improve existing tools, templates, and processes used by the R\&D Data Transformation team to identify improvement areas, track progress, and ensure business continuity of the function.

Key Accountabilities

Transformation Execution and Coordination

• Coordinate and deliver assigned transformation activities within defined workstreams — from data assessment and gap analysis through implementation, documentation, and handover — ensuring outputs meet quality standards and timelines.


• Apply the established transformation methodology (maturity models, prioritisation criteria, delivery playbooks) within assigned activities, flagging opportunities for improvement based on practical experience.


• Conduct current\-state assessments of R\&D data assets within assigned domains, documenting readiness, interoperability, and reuse maturity against defined criteria and producing clear findings for review.


• Work directly with data domain owners and R\&D functional teams to gather requirements, validate findings, and support the implementation of solutions addressing readiness, interoperability, and reuse gaps.


• Track and report progress, risks, and issues within assigned activities; support stage\-gate reviews by preparing materials and evidence of delivery against milestones.

• Support the implementation of FAIR principles, data standards, and ontologies within assigned R\&D domains, working hands\-on with domain teams to apply standards in practice.


• Identify and document interoperability barriers between R\&D systems, platforms, and data stores within assigned scope; propose solutions and escalate complex issues to senior team members.


• Maintain awareness of relevant industry standards (e.g., CDISC, OMOP, biomedical ontologies) and support their practical application within transformation activities.

• Execute cataloguing and metadata enrichment activities that increase discoverability and contextual richness of R\&D data assets within assigned domains.


• Collect, maintain, and report reuse metrics (e.g., asset utilisation, time\-to\-access, duplication reduction) for assigned domains, supporting evidence\-based prioritisation and value demonstration.


• Contribute to the development of reusable frameworks, templates, and guidance materials that support scalable adoption of data reuse practices.

• Develop and maintain tools, templates, and processes used by the R\&D Data Transformation team to conduct assessments, track transformation progress, and report outcomes.


• Identify areas for process improvement within existing transformation workflows; propose and implement enhancements that increase efficiency, consistency, or quality.


• Ensure business continuity of transformation processes and reporting within assigned scope, maintaining documentation and knowledge repositories to support team resilience.

• Solve complex problems within a variety of data transformation scenarios, applying analytical rigour and sound judgement to navigate ambiguity and deliver practical outcomes.


• Analyse R\&D data landscapes within assigned scope to identify improvement opportunities, synthesise findings into clear summaries, and present recommendations to senior team members.


• Support the preparation of business cases, progress reports, and stakeholder communications by providing accurate data, analysis, and evidence from assigned activities.

• Partner with Data Programmes (project leadership, change management, data automation) to coordinate transformation activity milestones with delivery timelines and change plans.


• Collaborate with peers within the R\&D Data Transformation team to share knowledge, maintain methodological consistency, and support coherent delivery across the portfolio.


• Build effective working relationships with R\&D functional teams and data domain contacts within assigned scope, maintaining regular communication and supporting co\-design activities.


• Contribute to Enterprise Data governance processes by ensuring transformation artefacts and documentation within assigned activities are transparent, complete, and aligned to enterprise standards.

• Degree in life sciences, informatics, data science, or a related discipline, or equivalent professional experience.


• Experience delivering data transformation, data management, or data quality initiatives within complex organi

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