Systems Architect

Virtusa; Greater London; On-site; GBP 90,000 - 150,000; Full time

Job summary

Virtusa Corporation seeks a Life Sciences Architecture Leader to drive end-to-end data modernization across R&D, Clinical Data, and Commercial analytics. You will lead discovery workshops, translate problems into scalable roadmaps, and govern programs across AWS, Azure, and GCP.

Collaboration with C-suite to align roadmaps and ensure compliant, reusable data assets is key. You will mentor teams, establish best practices for the Life Sciences COE, and push GenAI assets and lakehouse architectures

Qualifications

• 20+ years in architecture, applications, and big data analytics in Life Sciences.
• Domain expertise across Clinical Data, R&D, and Commercial Analytics.
• Strong leadership and stakeholder management across global teams.

Responsibilities

• Lead end-to-end data modernization programs across R&D, Clinical Data and Commercial ops.
• Define high-impact use cases and roadmaps for GenAI and lakehouse architectures.
• Provide governance and best-practices via the Life Sciences COE.
• Mentor technical teams and perform code reviews.

Skills

Data modernization

Cloud architecture

GenAI

Stakeholder management

Leadership

Architecture governance

Python/SQL

Tools

Databricks

Neo4j

AWS

Azure

GCP

Airflow

Terraform

Docker

Kubernetes

Jenkins

Job description

Life Sciences Leadership: Drive end-to-end data modernization across the Life Sciences value chain—spanning R&D, Clinical Data, and Commercial operations.Lead discovery workshops to define high-impact use cases that accelerate drug development and commercial outcomes.

Solution Strategy & Shaping: Translate complex business problems into scalable, value-led architecture roadmaps across AWS, Azure, and GCP.Lead end-to-end solutioning for high-value pursuits.

Architecture Leadership: Provide technical governance for critical programs. Drive the adoption of modern data platforms, including Lakehouse architectures for large-scale clinical and commercial data sets. Innovation & GenAI: Spearhead the development of GenAI assets (e.g., agentic workflows for R&D/IT) and Proof-of-Concepts (POCs) tailored to Life Sciences workflows.

Stakeholder Management: Partner with C-suite and senior stakeholders to align technical roadmaps with enterprise goals, ensuring compliance and data reusability across global research and commercial organizations.

Technical Enablement: Establish best practices for the Life Sciences Center of Excellence (COE), mentor technical teams, and perform rigorous code reviews.

Qualifications & Experience: 20+ years of experience across architecture, application development, and big data analytics, with significant tenure in the Life Sciences industry.

Domain Expertise: Proven track record in Life Sciences, specifically in Clinical Data, R&D, and Commercial Analytics. Deep understanding of the data challenges inherent in the Life Sciences value chain.

Core Architecture: Expertise in Data Modernization, Microservices, Cloud Architecture, and Lakehouse patterns.

Data & AI: Deep hands-on proficiency in Databricks (Spark, Spark, DLT), GenAI (Agent Core, Copilot Studio, Amazon Bedrock), and Graph Databases (Neo4j).

Cloud & Tools: Strong command of AWS (Lambda, Glue, EMR, MWAA, S3), Azure, Airflow, Terraform, Docker, Kubernetes, and Jenkins.

Programming: Advanced skills in Python, SQL, Scala, Java, and Shell Scripting. Leadership Competencies Strategic Advisory: Proven ability to lead post-technical win strategies and define long-term platform adoption roadmaps for enterprise-level Life Sciences programs.

Delivery Ownership: End-to-end accountability for complex architectural solutions, ensuring successful production go-lives in regulated environments.