Data & AI Architect – Life Sciences

Strong experience, ideally 7+ years, across Data, Analytics, Cloud or AI, with increasing responsibility in architecture and/or technical leadership.

Proven experience or strong domain knowledge in Life Sciences, with an understanding of the sector's key business processes, data ecosystems, and regulatory context.

Proven experience designing modern data solutions: data lake/lakehouse, data warehouse, streaming, APIs and integration, batch and real-time processing, modelling and governance.

Deep knowledge of at least one major hyperscaler (Azure, AWS or Google Cloud) and the ability to operate in multi-cloud environments.

Experience with modern data platforms such as Databricks, Microsoft Fabric, Snowflake, BigQuery or equivalent technologies.

Strong SQL skills and solid Python knowledge; practical understanding of Spark and distributed architectures.

Knowledge of AI/ML and GenAI architectures, including LLMs, RAG, agents, vector search, evaluation, guardrails, observability and industrialisation patterns.

Strong client-facing experience and the ability to communicate complex decisions to both technical and executive audiences.

Hands-on experience in technical pre-sales and in preparing and defending proposals.

Professional English at a minimum C1 level. Professional Spanish. Italian or Portuguese is a plus.

Availability to work in a hybrid model based in Barcelona and to travel occasionally depending on client/project needs.

Previous experience in technology or strategy consulting.

Commercial or business development experience within Data & AI.

Relevant certifications across Azure, AWS, Google Cloud, Databricks, Snowflake or other leading platforms.

Experience in Data Governance, Data Mesh, catalogues, MDM, data quality and data-product-oriented architectures.

Experience with MLOps, LLMOps, CI/CD, DevOps and platform automation.

Knowledge of FinOps and performance/cost optimisation.

Ability to build accelerators, assets and reusable solutions.

International experience, with a track record of working with stakeholders across different geographies and multicultural environments.

We are looking for a Manager / Senior Data & AI Architect to join our Barcelona team and help us grow one of BIP Iberia's strategic areas: the application of Data, Analytics and Artificial Intelligence within Life Sciences.

This is not a pure architecture role. We are looking for someone who combines strong technical depth with business understanding, client-facing skills and a pre-sales/commercial mindset. Someone who can design a robust architecture, defend it with a client, understand the business problem behind it and guide the team until the solution is successfully delivered and operational.

The role will be part of BIP's Global Data & AI team, with a strong focus on working closely with our local teams in Barcelona and across Spain, while collaborating with colleagues and specialists across Portugal, Italy and other BIP geographies.

Act as a Data & AI reference for Life Sciences, connecting strategy, business and technology. You will be involved from early client conversations and pre-sales through architecture definition, delivery and the evolution of production solutions.

You will also help build capabilities, reusable assets, propositions and references that strengthen our position in the Life Sciences market.

Design end-to-end Data, Analytics and AI architectures covering data platforms, lakehouse, integration, governance, advanced analytics, Machine Learning, GenAI and AI agents.

Translate Life Sciences business needs into concrete, scalable, secure and measurable technology solutions.

Act as a trusted technical advisor for CIOs, CDOs, Data & AI leaders, business stakeholders and architecture teams.

Play an active role in pre-sales: discovery, workshops, RFP/RFI responses, estimates, proposals, roadmaps, high-level architectures, demos, PoCs and executive presentations.

Work jointly with commercial leaders and Partners to identify and mature opportunities, bringing technical credibility and sector knowledge.

Provide technical leadership to multidisciplinary teams including Data Engineers, Analytics Engineers, Data Scientists, ML Engineers and AI specialists.

Define architecture standards and patterns across security, integration, observability, MLOps/LLMOps, governance and data quality.

Support solutions through production, ensuring operability, performance, security, cost control and long-term scalability.

Contribute to the growth of the Data & AI practice in Barcelona and to BIP's international Life Sciences collaboration.

Mentor junior colleagues and raise the technical bar through design reviews, best practices and knowledge sharing.

Relevant experience or strong knowledge of the Life Sciences sector is important. The successful candidate should understand key business processes, industry challenges and the regulatory context in which clients operate.

Experience in Pharma, Biotech, MedTech, Healthcare or related environments.

Understanding of Data & AI use cases across R&D, clinical, medical affairs, commercial, market access, supply chain, manufacturing, quality or patient/healthcare analytics.

Ability to work with sensitive data and regulated environments, with awareness of privacy, traceability, quality, governance and compliance principles.

Knowledge of scientific, clinical, commercial or healthcare data ecosystems will be highly valued.

Consulting mindset and client orientation: listen, structure ambiguous problems and turn them into actionable decisions.

Technical credibility: ability to go deep when required while maintaining an end-to-end perspective.

Business orientation: understanding that architecture is a means to create impact, not an end in itself.

Communication and influencing skills: confidently present and defend proposals to technical teams, business stakeholders and senior management.

Commercial and pre-sales mindset: comfortable participating in opportunity discussions and shaping a compelling value proposition.

Leadership without hierarchy: ability to mobilise teams, make decisions and build trust.

Pragmatism, autonomy and end-to-end ownership.

Curiosity and continuous learning in a fast-moving technology environment.