GCP Data Engineer (Java, Spark, ETL)

Staffworx
Edinburgh, Scotland
12 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer

Synthesia London, United Kingdom
Hybrid

AI / Machine Learning Engineer

The Digital Bench Ltd Australia
£70,000 – £95,000 pa

Senior Machine Learning Engineer

Platform Recruitment Cambridge, United Kingdom

AI / ML Engineer

Maxwell Bond Manchester, United Kingdom

Data Platform Solutions Architect (Professional Services)

Databricks London, United Kingdom
£40,000 – £80,000 pa Hybrid

Data Platform Solutions Architect (Professional Services) - Emerging Enterprise & DNB

Databricks London, United Kingdom
Posted
3 May 2025 (12 months ago)

Future Talent Pool - GCP Data Engineer, London, hybrid role - digital Google Cloud transformation programme


  • Proficiency in programming languages such as Python, PySpark and Java
  • develop ETL processes for Data ingestion & preparation
  • SparkSQL
  • CloudRun, DataFlow, CloudStorage
  • GCP BigQuery
  • Google Cloud Platform Data Studio
  • Unix/Linux Platform
  • Version control tools (Git, GitHub), automated deployment tools
  • Google Cloud Platform services, Pub/Sub, BigQuery Streaming and related technologies.
  • Deep understanding of real-time data processing and event-driven architectures.
  • Familiarity with data orchestration tools Google Cloud Platform cloud composer.
  • Google Cloud Platform certification(s) is a strong advantage.
  • Develop, implement, and optimize real-time data processing workflows using Google Cloud Platform services such as Dataflow, Pub/Sub, and BigQuery Streaming.


6 months initial, likely long term extensions


This advert was posted by Staffworx Limited - a UK based recruitment consultancy supporting the global E-commerce, software & consulting sectors. Services advertised by Staffworx are those of an Agency and/or an Employment Business.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Where to Advertise Machine Learning Jobs in the UK (2026 Guide)

Advertising machine learning jobs in the UK requires a different approach to most technical hiring. The candidate pool is small, highly specialised and in demand across AI labs, financial services, healthcare, autonomous systems and consumer technology simultaneously. Machine learning engineers and researchers move between roles through professional networks, conference communities and specialist platforms — not general job boards where ML roles compete with unrelated software engineering positions for the same audience. This guide, published by MachineLearningJobs.co.uk, covers where to advertise machine learning roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

New Machine Learning Employers to Watch in 2026: UK and Global Companies Driving ML Innovation

Machine learning (ML) has transitioned from a specialised field into a core business capability. In 2026, organisations across healthcare, finance, robotics, autonomous systems, natural language processing, and analytics are expanding their machine learning teams to build scalable intelligent products and services. For professionals exploring opportunities on www.MachineLearningJobs.co.uk , understanding the companies that are scaling, winning investment, or securing high‑impact contracts is crucial. This article highlights the new and high‑growth machine learning employers to watch in 2026, focusing on UK innovators, international firms with significant UK presence, and global platforms investing in machine learning talent locally.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.