Key Responsibilities:

1. 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.

2. Life Sciences Domain Architecture:

- Provide architectural leadership across Research & Discovery (scientific data, lab systems, bioinformatics platforms).

- 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.

3. 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.

4. 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.

5. 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.

6. 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.

Required Skills & Experience:

1. 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), and Cloud Architecture (AWS / Azure / GCP).

- Experience modernizing legacy life sciences systems.

2. Life Sciences Domain Experience:

- 46+ 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.

3. 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.

4. 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.