Roles and Responsibility

Define and maintain enterprise architecture vision, principles, standards, and roadmaps aligned with life sciences business strategy.
Develop current-state and target-state architectures across business, application, data, and technology domains.
Drive architecture for digital transformation initiatives such as data platforms, AI/ML enablement, cloud migration, and legacy modernization.
Align IT architecture with R&D, Clinical, Manufacturing, Quality, Regulatory, and Commercial strategies.
Provide architectural leadership across Research & Discovery, ensuring architecture supports end-to-end data flow across the life sciences value chain.
Ensure architecture complies with GxP, 21 CFR Part 11, GDPR, HIPAA, and data privacy regulations, embedding security, auditability, traceability, and validation requirements into design.
Partner with business leaders, scientific teams, and IT leadership to translate strategy into executable architecture, acting as a trusted advisor on technology choices and trade-offs.
Support large-scale programs and portfolios with architecture oversight, mentoring Solution Architects and technical teams on best practices.
Promote reuse of standards, platforms, and reference architectures, contributing to improving enterprise architecture maturity.

Job Requirements

Strong experience with Enterprise Architecture frameworks (TOGAF or equivalent).
Hands-on experience in Application Architecture (Monoliths, Microservices), Data Architecture (Data Warehousing, Data Lakes, MDM), Integration Architecture (APIs, ESB, Event-driven), and Cloud Architecture (AWS / Azure / GCP).
Experience modernizing legacy life sciences systems and familiarity with regulated environments (GxP).
Strong stakeholder management and communication skills, with the ability to influence across business, scientific, and IT teams.
Strategic mindset with strong problem-solving ability and comfort working with senior leadership.
Ability to work in a fast-paced environment and adapt to changing priorities.
Experience with tools such as Sparx EA, LeanIX, ArchiMate, or equivalents.
Familiarity with clinical, scientific, and manufacturing data landscapes.
Tools & Platforms: AWS / Azure / GCP, Data & analytics platforms: Data Lakes, Warehouses, Analytics tools, Integration platforms: APIs, Messaging, Middleware.
Soft Skills: Strong stakeholder management and communication skills, ability to influence across business, scientific, and IT teams, strategic mindset with strong problem-solving ability, comfortable working with senior leadership.

Enterprise Architect - Life Sciences

Job Description