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)

- 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.

Required Skills & Experience :

Architecture & Technical Skills :

- Strong experience with Enterprise Architecture frameworks (TOGAF or equivalent).

- Hands-on experience in :

1. Application Architecture (Monoliths, Microservices)

2. Data Architecture (Data Warehousing, Data Lakes, MDM)

3. Integration Architecture (APIs, ESB, Event-driven)

4. Cloud Architecture (AWS / Azure / GCP)

- Experience modernizing legacy life sciences systems.

Life Sciences Domain Experience :

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

- Strong understanding of regulated environments (GxP).

- Experience with life sciences platforms such as :

1. 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

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.