Data Engineer

Data Freelance Hub; Greater London; Hybrid; GBP 60,000 - 80,000; Full time

Job summary

A leading data consultancy is seeking an experienced Data Engineer for a 6-month contract in Central London. The role involves designing and managing cloud data pipelines and requires strong skills in Python and cloud object storage (GCS/S3), along with practical experience in PyTorch. Ideal candidates will have a strong commercial background in data engineering and an interest in ML workflows. This position is based in Central London, with an agile working pattern of 2 to 3 days in-office, offering £750 per day.

Qualifications

• Strong commercial experience as a Data Engineer.
• Hands-on experience with cloud object storage (GCS preferred, or AWS S3).
• Practical PyTorch experience for training pipelines and dataset handling.

Responsibilities

• Design, build, and maintain scalable cloud data pipelines supporting ML workloads.
• Manage large volumes of unstructured data using cloud object storage.
• Support PyTorch-based data loading and dataset management.

Skills

Python development

Cloud object storage (GCS/S3)

PyTorch

Tools

BigQuery

SQL databases

Job description

⭐ - Featured Role | Apply direct with Data Freelance Hub

This role is for a Data Engineer on a 6-month contract, paying £750 per day, based in Central London (2/3 days in-office). Key skills include strong Python, cloud object storage (GCS/S3), and PyTorch experience.

Location: London, England, Central London

Contract: 6 months | Rate: £750 per day | Inside IR35

Key Responsibilities

• Design, build, and maintain scalable cloud data pipelines supporting ML workloads
• Manage large volumes of unstructured data using cloud object storage (GCS / S3)
• Support PyTorch-based data loading and dataset management in production environments
• Work closely with ML practitioners to enable training and inference pipelines
• Ensure efficient memory usage and performance when handling large datasets
• Integrate data from SQL-based systems into cloud and ML pipelines
• Apply best practices around reliability, monitoring, and scalability

Required Experience

• Strong commercial experience as a Data Engineer
• Strong Python development skills
• Hands‑on experience with cloud object storage (GCS preferred, or AWS S3)
• Practical PyTorch experience (e.g. supporting training pipelines, dataset handling, data loaders)
• Experience working in cloud environments with large‑scale file‑based data

Desired Experience

• BigQuery (GCP)
• SQL databases (Microsoft SQL Server preferred; PostgreSQL also acceptable)
• Memory management and performance optimisation
• Exposure to ML workflows (without being a dedicated ML Engineer)

Nice to Have

• Broader GCP experience (Cloud Run, Cloud SQL, Cloud Scheduler, etc.)
• Pharma or life sciences domain exposure (or strong interest in the space)
• TensorFlow experience (acceptable alternative to PyTorch)

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