GCP Data Engineer
£500 - £550 per day inside IR35
6-month contract
Hybrid working in London
We're working with a global healthcare and AI research organisation at the forefront of applying data engineering and machine learning to accelerate scientific discovery. Their work supports large-scale, domain-specific datasets that power research into life-changing treatments.
They're now looking for a GCP Data Engineer to join a multidisciplinary team responsible for building and operating robust, cloud-native data infrastructure that supports ML workloads, particularly PyTorch-based pipelines.
The RoleYou'll focus on designing, building, and maintaining scalable data pipelines and storage systems in BigQuery, supporting ML teams by enabling efficient data loading, dataset management, and cloud-based training workflows.
Key ResponsibilitiesDesign and build cloud-native data pipelines using Python on GCP
Manage large-scale object storage for unstructured data within BigQuery
Build and optimise data integrations with BigQuery and SQL databases
Ensure efficient memory usage and performance when handling large datasetsImplement monitoring, testing, and documentation to ensure production-grade reliability
Participate in agile ceremonies, code reviews, and technical design discussions
Strong Python development experience
Hands-on experience with cloud object storage for unstructured data within BigQuery
PyTorch experience, particularly:
Dataset management
Data loading pipelines
Running PyTorch workloads in cloud environments We are not looking for years of PyTorch experience - one or two substantial 6-12 month projects is ideal
5+ years cloud experience, ideally working with large numbers of files in cloud buckets
Experience with additional GCP services, such as:
Cloud Run
Cloud SQL
Cloud Scheduler
Exposure to machine learning workflows (not ML engineering)
Some pharma or life sciences experience, or a genuine interest in working with domain-specific scientific data
Please send your CV