GCP Data Engineer

City of London
7 months ago
Applications closed

Related Jobs

View all jobs

GCP Data Engineer

GCP Data Engineer

Lead GCP Data Engineer

Principal GCP Data Engineer

Principal GCP Data Engineer

Principal GCP Data Engineer

A specialist reinsurance broker is seeking a Data Engineer with Google Cloud Platform (GCP) experience to join their growing team in Central London. This is a hybrid role, requiring 2-3 days per week in the office.

This is a modern, digitally native business with no legacy systems - a rare opportunity to work in a clean, forward-thinking tech environment. You'll be joining a dynamic and fast-paced team that values innovation, adaptability, and continuous improvement.

Key responsibilities will include:

Lead and support the migration from Azure to Google Cloud Platform (GCP), including BigQuery
Collaborate with stakeholders to understand data needs and ensure smooth transition and integration
Become the internal GCP subject matter expert, with direct support from Google
Contribute to the adoption of AI and emerging technologies post-migration
Thrive in a fast-evolving environment with minimal legacy constraintsRequirements :

Proven experience as a Data Engineer.
Hands-on experience with cloud migrations (on-prem to cloud or cloud-to-cloud).
Strong knowledge of GCP, including BigQuery.
Experience in Financial Services is desirable but not essential
Exposure to AI technologies is a plus
Excellent communication and stakeholder management skills
Comfortable working in a dynamic, unstructured environmentBenefits:

Salary up to £75,000 depending on experience
Performance-related bonus
Unlimited holidays
Contributory pension scheme
Private healthcare

Please Note: This is a permanent role for UK residents only. This role does not offer Sponsorship. You must have the right to work in the UK with no restrictions. Some of our roles may be subject to successful background checks including a DBS and Credit Check.

Tenth Revolution Group / Nigel Frank is the UK's leading recruiter for Data and AI roles. We proudly sponsor SQLBits and the London Power BI User Group. For a confidential discussion about this role or your job search, contact

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.

Careers

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

Jobs

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

Education

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.