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# System Architect

- **Company:** Virtusa
- **Location:** London, UK
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Artificial Intelligence, Airflow, Amazon Web Services, Amazon S3, Microsoft Azure, Big Data, Clinical Data Repository, Cloud Engineering, Code Review, Data Infrastructure, Data Transformation, Graph Database, Python (Programming Language), Neo4j, Scala (Programming Language), Shell Script, Software Engineering, SQL Databases, Systems Architecture, Apache Spark, Pyspark, Kubernetes, Terraform, Docker, Databricks, Microservices
- **Published:** September 9, 2026
- **Apply:** https://find.jobs/jobs-near-me/apply/ats-redirect/?id=2963128665-2

## About the Role

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. Technical ExpertiseExperience: 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, PySpark, 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 CompetenciesStrategic 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.Technical Enthusiasm: A continuous learner, proactive in navigating new product innovations and
bridging the gap between Life Sciences business priorities and engineering feasibility.Work Experience 1530yearsJob SummaryJob number: P-101329Profession: OtherExperience: 1530years