The Enterprise Architect (EA) - Life Sciences is responsible for defining and governing enterprise-wide architecture aligned to business strategy, regulatory requirements, and scientific workflows. This role ensures scalable, compliant, and interoperable architecture solutions across R&D, Clinical, Manufacturing, Quality, Regulatory, and Commercial domains.

The EA partners with business, scientific, and IT stakeholders to drive digital transformation, data platforms, cloud adoption, and modernization initiatives across the life sciences value chain. The candidate should have 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.

- Ideal candidate should have strong
Architecture & Technical Skills.

- 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),

Cloud Architecture (AWS / Azure / GCP)

- Experience modernizing legacy life sciences systems.

Key Responsibilities :

Enterprise Architecture & Strategy :

- 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.

Life Sciences Domain Architecture :

Provide architectural leadership across :

1. Research & Discovery (scientific data, lab systems, bioinformatics platforms)

2. Clinical Development (CTMS, EDC, eTMF, safety systems)

3. Manufacturing & Quality (MES, LIMS, QMS, serialization)

4. Regulatory & Pharmacovigilance

5. Commercial & Medical Affairs

- Ensure architecture supports end-to-end data flow across the life sciences value chain.

- Enable FAIR data principles, data reuse, and interoperability across scientific and enterprise platforms.

- Guide integration of COTS life sciences platforms with enterprise systems.

Data, Cloud & Platform Architecture :

- Define enterprise data architecture supporting structured, semi-structured, and unstructured scientific data.

- Guide architecture for data lakes, data warehouses, analytics, and AI/ML platforms.

- Support cloud and hybrid architectures (AWS / Azure / GCP) for regulated workloads.

- Define integration strategies using APIs, event-driven architectures, and messaging.

Governance, Compliance & Security :

- Ensure architecture complies with GxP, 21 CFR Part 11, GDPR, HIPAA, and data privacy regulations.

- Embed security, auditability, traceability, and validation requirements into architecture designs.

- Participate in Architecture Review Boards (ARB) and governance forums.

- Identify and mitigate architecture and compliance risks.

Stakeholder & Program Engagement :

- Partner with business leaders, scientific teams, and IT leadership to translate strategy into executable architecture.

- Act as a trusted advisor to senior stakeholders on technology choices, trade-offs, and risk.

- Support large-scale programs and portfolios with architecture oversight.

Mentoring & Capability Building :

- Mentor Solution Architects and technical teams on enterprise and life sciences architecture best practices.

- Promote reuse of standards, platforms, and reference architectures.

- Contribute to improving enterprise architecture maturity.

Life Sciences Domain Experience :

- 4-6+ years of experience in Life Sciences / Pharma / Healthcare IT.

- Strong understanding of regulated environments (GxP).

- Experience with life sciences platforms such as : LIMS, ELN, CTMS, EDC, eTMF, Safety systems, MES, QMS (any combination)

- Familiarity with clinical, scientific, and manufacturing data landscapes.

Tools & Platforms (Indicative) :

- Architecture tools : Sparx EA, LeanIX, ArchiMate (or equivalents)

- Cloud platforms : AWS / Azure / GCP

- Data & analytics platforms : Data Lakes, Warehouses, Analytics tools

- Integration platforms : APIs, Messaging, Middleware

Qualifications :

- Bachelors degree in Engineering / Technology (Masters preferred).

- TOGAF or equivalent architecture certification (preferred).

- Cloud certification is a plus.