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.

The Role

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.

Key Responsibilities

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

Tech Stack & Experience Must Have

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

...