At a Glance
- Tasks: Design and build scalable data pipelines in Google Cloud for ML workloads.
- Company: Join a leading global healthcare and AI research organisation.
- Benefits: Competitive daily rate, hybrid working, and opportunity to impact scientific discovery.
- Other info: Collaborative team environment with agile practices and growth opportunities.
- Why this job: Be at the forefront of data engineering and machine learning in healthcare.
- Qualifications: Strong Python skills and experience with cloud storage and PyTorch.
The predicted salary is between 63000 - 77000 £ per year.
£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
- Running PyTorch workloads in cloud environments
- 5+ years cloud experience, ideally working with large numbers of files in cloud buckets
Nice to Have
- 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
GCP Data Engineer in London employer: Harnham - Data & Analytics Recruitment Careers
As a leading consumer retail organisation based in London, we pride ourselves on fostering a dynamic and inclusive work culture that champions innovation and collaboration. Our commitment to employee growth is evident through tailored development programmes and the opportunity to lead transformative digital initiatives, all while enjoying a competitive salary and bonus structure. Join us to be part of a forward-thinking team that values your contributions and empowers you to drive meaningful change in a rapidly evolving market.
Contact Details:
Harnham - Data & Analytics Recruitment Careers Recruitment Team
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We think this is how you could land GCP Data Engineer in London
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We think you need these skills to ace GCP Data Engineer in London
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