R&D Data Architect

About the role

CSL R&D is driving significant transformation — accelerating its data and AI ambitions in a way that demands architecture thinking rooted in business value, not just technical delivery. The R&D Data Architect is a brand new role, created to make that ambition a reality. This role is responsible for designing and managing the data architecture that connects scientific discovery, clinical development, regulatory compliance, and operational efficiency — across both internal and external data sources.

The R&D Data Architect defines and promotes the future-state vision for R&D data architecture (City Plan) as well as providing technical oversight to data engineers implementing the data architecture vision. The role is accountable for designing the overall R&D architecture for data, integration, automation, and AI, and serves as the interface between R&D and other enterprise I&T functions. This position establishes the enterprise data model, master data sources, and integration between platforms, and requires some technical implementation experience, such as delivering Data Products or a semantic layer. This is a key role as R&D transforms into a Product operating model and drives insight from its data with increasing speed and innovation.

Responsibilities

• Lead the design, development, and evolution of R&D data architecture
• Collaborate with R&D Architecture Lead, Head R&D Data Strategy, Digital Business Partners, scientists, engineers, and Product teams to align data architecture with R&D goals and overall business strategy
• Provide technical leadership and oversight to data engineering teams as they implement the data architecture vision
• Direct how foundational data architecture is set up by driving the adoption of modern data architecture approaches including Data Mesh, Data Products, Semantic Layers, and Knowledge Graphs
• Evaluate emerging data trends and propose innovations to enhance R&D productivity and enable next-generation research solutions
• Ensure data architectural compliance with security, scalability, and regulatory standards, ensuring data meets operational and compliance requirements
• Mentor technical teams, promoting best practices in data architecture across projects and teams
• Partner with the I&T Enterprise Data teams to ensure alignment of R&D with CSL strategic direction

Key Deliverables

• R&D data architecture City Plan
• End-to-end data flow models for key R&D data entities, detailing how data are generated, ingested, and flow across operational and business applications, including a blueprint that enables the execution of data products
• Comprehensive data architectural documentation, roadmaps, and reference patterns
• Integration and platform data architecture designs
• Automation and AI data architecture designs
• Conceptual, logical, canonical, and semantic data models across R&D domains, in partnership with relevant stakeholders

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field
• Proven track record of creating integration patterns, data flow models, enterprise data models, and cloud-native data architectures
• Implementation experience delivering data products, integrations, semantic layers
• 8+ years of experience in data architecture, with at least 3 years in an R&D biotech or pharma environment
• Experience with R&D platforms in biotech or pharma, including knowledge of clinical system data flow and data product consumption models
• Data aggregator vendor landscape awareness and working experience
• Professional experience and knowledge of best practice in data modelling techniques
• High learning agility with strong motivation to maintain leading-edge data architecture knowledge and capability
• Excellent communication and leadership skills, with the ability to engage cross-functional teams and communicate complex data architectural concepts clearly
• Decisive, focused on priorities, demonstrating high engagement levels and the ability to communicate upwards with no surprises

Skills

• Desirable experience working with knowledge graphs and semantic and logic layers
• Knowledge of TOGAF