Lead the implementation, configuration, and optimization of laboratory informatics systems (e.g., ELN, LIMS, SDMS) to enhance scientific workflows.
Partner with R&D scientists to translate experimental processes into structured, scalable digital solutions.
Design and implement data models, templates, metadata structures, and workflows aligned with FAIR (Findable, Accessible, Interoperable, Reusable) data principles.
Build and maintain integrations between lab platforms, analytics tools, automation systems, and cloud-based environments using APIs and middleware.
Develop robust data flows that improve interoperability, reduce manual effort, and ensure high-quality experimental data capture.
Contribute to digital architecture discussions and help shape the evolution of Lonza’s R&D data ecosystem.
Deliver user training, documentation, and ongoing support to drive adoption and continuous improvement of digital lab solutions.

MSc (or equivalent) in Bioinformatics, Biology, Chemistry, Engineering, or a related scientific field.
Experience working within pharma, biotech, or life sciences R&D environments.
Hands-on experience implementing or optimizing laboratory informatics systems (e.g., ELN, LIMS, SDMS).
Strong understanding of scientific workflows and experimental data lifecycle management.
Experience with data modelling concepts and metadata standards; familiarity with FAIR data principles is highly desirable.
Programming or scripting experience (e.g., Python, R, SQL) and experience integrating systems using APIs (REST, GraphQL).
Strong communication skills with the ability to collaborate effectively across scientific and technical teams.
Experience with cloud platforms (Azure, AWS, GCP), laboratory automation systems, or bioinformatics data pipelines would be an advantage.

Lab Informatics Engineer

Key skills