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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # data engineer - **Company:** Tropic Biosciences - **Location:** Norwich, UK - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Microsoft Azure, Bioinformatics, Business Systems, Databases, Continuous Integration, Data Architecture, Information Engineering, Extract Transform Load (ETL), Data Sharing, Data Systems, Graph Database, Python (Programming Language), Laboratory Information Management Systems, Machine Learning, Operational Data Store, Operational Databases, Software Engineering, SQL Databases, Workflow Management Systems, Google Cloud, Data Layers, Build Management, Data Pipelines - **Published:** September 10, 2026 - **Apply:** https://startup.jobs/scientific-data-platform-engineer-tropic-biosciences-9966699 ## About the Role * 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. * Experience designing data models and data architectures across multiple systems and building and operating production-quality ETL/ELT pipelines and automated data workflows. * Experience integrating heterogeneous data sources, databases and APIs. * Experience with workflow orchestration tooling (e.g. Airflow, Dagster or dbt) for scheduling and operating production data pipelines. * Good understanding of data quality, metadata, lineage, testing and reproducibility. * Ability to evaluate technical options and make pragmatic, scalable and cost-aware architecture decisions. * Strong problem-solving skills and the ability to translate ambiguous requirements into implementable solutions. * Strong communication and collaboration skills across technical and non-technical teams. Desirable skills and experience Experience in one or more of the following would be an advantage, but is not required: * Scientific, biotechnology, life-sciences or other R&D data. * Azure and/or Google Cloud Platform. * ELN or LIMS platforms such as Benchling. * Preparing data for analytics, machine learning or AI applications. * Semantic modelling, ontologies or knowledge graphs. * CI/CD, infrastructure-as-code or other modern software-engineering practices ## Description 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. What you will do * 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. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Why Your AI Agent Keeps Hallucinating Your Data: Building Deterministic Context Layers](https://www.wearedevelopers.com/videos/2055-why-your-ai-agent-keeps-hallucinating-your-data-building-deterministic-context-layers) - [Kubernetes and Microservices with Multi-Model Databases](https://www.wearedevelopers.com/videos/382-kubernetes-and-microservices-with-multi-model-databases) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Fault Tolerance and Consistency at Scale: Harnessing the Power of Distributed SQL Databases](https://www.wearedevelopers.com/videos/1146-fault-tolerance-and-consistency-at-scale-harnessing-the-power-of-distributed-sql-databases) - [How to govern Vibe Coding for the Enterprise](https://www.wearedevelopers.com/videos/100290-how-to-govern-vibe-coding-for-the-enterprise) ## Related Articles - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [Software Engineer Salary London](https://www.wearedevelopers.com/magazine/252-software-engineer-salary-london) - [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know)