D&AI DELIVERY MANAGER

• Location: BARCELONA
• We’re building the future of medical dermatology by focusing on unmet patient needs and giving people the space to think independently, take ownership and make an impact that matters.
• Our purpose is simple: to transform patients’ lives by addressing real needs. We work with care, act with courage, keep things simple and focus our innovation where it makes a difference.
• Recognised as a Top Employer in Spain since 2008 and in Germany since 2025, we continue to invest in an environment where people can grow and move forward.
• If you care differently, you belong here.

Mission

The Data & AI Delivery Manager is responsible for leading the delivery and continuous evolution of Data, Analytics, AI and Generative AI products and services, ensuring they generate measurable business value.

Acting as a bridge between Business and IT, this role drives execution, adoption and value realization across the Data & AI portfolio. Working with a high degree of autonomy, the Delivery Manager coordinates internal teams, external partners and key stakeholders to ensure successful outcomes and continuous improvement.

Key Responsibilities

• Lead the end-to-end delivery of Data, Analytics, AI and Generative AI initiatives aligned with business priorities.
• Manage Data & AI products and services throughout their lifecycle, balancing value, budget, resources and delivery commitments.
• Partner with business stakeholders, Product Owners and Sponsors to shape demand, challenge requirements and prioritize initiatives.
• Drive product adoption, value realization and continuous improvement based on business feedback and usage insights.
• Promote agile delivery practices and outcome-driven ways of working.
• Define and track success metrics, KPIs and OKRs aligned with business objectives.
• Ensure effective governance, planning, risk management and stakeholder alignment.
• Manage external suppliers and technology partners, ensuring delivery quality and performance.

Required Experience

• 10+ years of experience in IT, Digital, Data & Analytics or AI-related delivery roles.
• Proven experience leading complex initiatives in agile and cross-functional environments.
• Experience delivering Data, Analytics, AI and/or Generative AI solutions in enterprise settings.
• Strong stakeholder management, influencing and relationship-building skills.
• Experience driving adoption, change management and business value realization.
• Experience managing demand pipelines, product roadmaps and prioritization processes.
• Experience collaborating with business leaders, Product Owners, Architecture, Security, Legal and external providers.
• Experience managing vendors and service partners.
• Fluent in English.

Technical & AI Knowledge

• Good understanding of modern Data & AI platforms, architectures and delivery models.
• Experience with technologies such as Azure, Databricks, Power BI and Power Platform.
• Familiarity with Generative AI solutions and enterprise AI platforms such as Microsoft Copilot, Copilot Studio, Claude or similar technologies.
• Understanding of AI delivery patterns including AI Assistants, AI Agents and Retrieval-Augmented Generation (RAG).
• Awareness of Responsible AI, data governance, security and compliance requirements.
• Ability to translate technology capabilities into business outcomes and adoption.
• Additional Experience in Pharmaceutical R&D Data & Analytics
• Experience delivering Data, Analytics and AI initiatives within Pharmaceutical R&D organizations.
• Familiarity with scientific data domains, including genomics, transcriptomics, proteomics, single-cell and multi-omics datasets, as well as related analytical and bioinformatics workflows.
• Experience supporting preclinical research initiatives such as target discovery, target validation and scientific evidence generation.
• Experience delivering data-driven and AI-enabled initiatives supporting Target Story, Indication Expansion and other research insight generation processes.
• Experience working with platforms supporting clinical development, laboratory data integration and research data management.
• Proven ability to collaborate with multidisciplinary teams including scientists, bioinformaticians, data engineers and business stakeholders.
• Strong understanding of FAIR Data Principles, scientific data governance and regulated cloud-based research environments.

Key Capabilities

• Strong business and value-oriented mindset.
• Product-focused approach with emphasis on adoption and outcomes.
• Ability to influence stakeholders and drive alignment across business and technology teams.
• Strong delivery, planning and prioritization skills.
• Collaborative leadership style with the ability to work effectively without direct authority.