Scientific Data Platform Engineer

We are looking for our first dedicated data engineer to define and build the shared data foundation for a complex, high-value scientific estate .

Tropic has built a decade of proprietary scientific evidence spanning gene-editing outcomes, field trials, genotyping, phenotyping and product decisions.

This role will make that evidence more connected, traceable and reusable, enabling scientists and AI applications to learn from previous results and improve future crop-development decisions.

You will define the architecture that connects Tropic's scientific and operational data through shared identifiers, metadata, lineage and governance.

Working with Bioinformatics, IT and business data owners, you will recommend the data engineering stack to support AI programmes across science, commercial, pipeline and supply.

Within your first year, you will launch the first connected scientific data layer and operationalise the shared architecture supporting Tropic's AI programs connecting genome-editing designs with experimental, genotyping and phenotypic outcomes so that we can systematically learn from our own data and improve future design decisions. The architecture developed through this work will provide a foundation for wider scientific, operational, analytics and AI applications.

• Design and build scalable data architecture, models, pipelines and integrations across scientific and business systems.
• Establish consistent approaches to identifiers, metadata, data quality, lineage and traceability.
• Create reusable data foundations that support bioinformatics, analytics, machine learning and AI.
• Evaluate technical options and help establish data-engineering standards and best practices.
• Work closely with scientists, Bioinformatics and IT to translate complex questions into practical data solutions.

Essential skills and experience

• Around five years' experience in data engineering, software engineering or a related data-platform role, with experience taking ownership of technical design.
• Strong hands-on experience with Python and SQL.