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.
Role Overview
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. You will define and promote the future-state vision for R&D data architecture, own the enterprise data model, define master data sources, and ensure integration across platforms, while also serving as the interface between R&D and enterprise IT.
Responsibilities
- Lead the design, development, and evolution of the R&D data architecture.
- Collaborate with the R&D Architecture Lead, Head of R&D Data Strategy, Digital Business Partners, scientists, engineers, and product teams to align data architecture with R&D goals and overall business strategy.
- Evaluate emerging data trends and propose innovations to enhance R&D productivity and enable next‑generation research solutions.
- Ensure architectural compliance with security, scalability, and regulatory standards.
- Mentor technical teams, promoting best practices in data architecture across projects.
- Partner with I&T Enterprise Data teams to ensure R&D aligns with CSL's 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 and move across operational and business applications.
- Comprehensive data architectural documentation, roadmaps and reference patterns.
- Integration and platform data architecture designs.
- Automation and AI data architecture designs.
Skills and Experience
- Bachelor's or Master’s degree in Computer Science, Engineering, or a related technical field.
- 8+ years of experience in data architecture, with at least 3 years in an R&D biotech or pharma environment.
- Proven track record in integration patterns, data flow models, enterprise data models and cloud‑native data architectures.
- Experience with R&D platforms in biotech or pharma, including clinical system data flow and data product consumption models.
- Awareness of the data aggregator vendor landscape and hands‑on working experience.
- Strong knowledge of data modelling best practices.
- Ability to operate at strategic and technical levels, communicating complex architectural concepts clearly to cross‑functional audiences and engaging upwards without surprises.
- High learning agility and genuine motivation to stay at the leading edge of data architecture.
- Experience with knowledge graphs, semantic and logic layers is desirable, as is TOGAF familiarity.
Equal Opportunity Employer. If you are an individual with a disability and need a reasonable accommodation for any part of the application process, please let us know.
