GCP Data Engineer

GCP Data Engineer

£700 - £750 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.

You'll focus on designing, building, and maintaining scalable data pipelines and storage systems in Google Cloud, supporting ML teams by enabling efficient data loading, dataset management, and cloud-based training workflows.

You'll work closely with ML engineers and researchers, ensuring that large volumes of unstructured and structured data can be reliably accessed, processed, and consumed by PyTorch-based systems.

• Design and build cloud-native data pipelines using Python on GCP

• Manage large-scale object storage for unstructured data (Google Cloud Storage preferred)

• Support PyTorch-based workflows, particularly around data loading and dataset management in the cloud

• Build and optimise data integrations with BigQuery and SQL databases

• Ensure efficient memory usage and performance when handling large datasets

• Collaborate with ML engineers to support training and experimentation pipelines (without owning model development)

• Implement 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
  (Google Cloud Storage preferred; AWS S3 also acceptable)

• 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