R&D Data Architect

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 is responsible for designing and managing the data architecture to facilitate scientific discoveries, clinical development, regulatory compliance, and operational efficiency across both internal and external data sources. The role 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 R&D Data Architect is accountable for designing the overall R&D architecture for data, integration, automation and AI as well as being 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. The role also requires some technical implementation experience, for example in 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.

Key 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 Skills & Experience
• 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
• Desirable to bring experience working with knowledge graphs and semantic and logic layers, as well as knowledge of TOGAF