Data Engineer - Surrey - Hybrid

Woking
9 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

As a Data Engineer, you will design, build, and maintain data pipelines and solutions to support business needs. This role involves leveraging your technical expertise to enable data-driven decision-making.

Client Details

Data Engineer - Surrey - Hybrid

Our client is a well-established organisation undergoing a significant digital and data transformation. With a focus on innovation and technology, they are investing in building modern, cloud-based data capabilities to drive smarter decision-making, improve customer experience, and support future growth. This is an exciting time to join a business that is placing data at the heart of its strategy and creating opportunities for impactful work across the organisation

Description

Data Engineer - Surrey - Hybrid

As the Data Engineer you will help design, build, and scale a modern Azure-based data platform. This is your chance to play a key role in shaping how data is used to drive smarter decisions and real business impact.

Develop, maintain, and optimise data pipelines and workflows.
Collaborate with stakeholders to gather and analyse data requirements.
Ensure data accuracy, security, and compliance with industry standards.
Integrate data from multiple sources to create unified datasets.
Implement and manage data storage solutions.
Monitor and troubleshoot data systems to ensure smooth operations.
Provide technical guidance on data engineering best practices.
Contribute to the development of data strategies and architectures.Profile

Data Engineer - Surrey - Hybrid

A successful Data Engineer should have:

Experience with Azure Data Factory, Azure Synapse, Azure SQL, or Azure Data Lake.
Hands-on knowledge of the ETL process and working with large datasets.
Understanding of dimensional modelling and data warehousing principles.
Familiarity with CI/CD pipelines or monitoring tools for data processes.
Solid skills in SQL and basic knowledge of Python scripting.
Exposure to Microsoft Fabric (a plus, but not essential)Job Offer

Data Engineer - Surrey - Hybrid

Discover a dynamic role where you'll work with cutting-edge Azure technology, collaborate across teams, and enjoy real opportunities for growth and impact.

Competitive salary in the range of £55,000 - £70,000 per annum.
Standard benefits package, including pension contributions and health coverage.
Generous holiday leave to support work-life balance.
Opportunities to work on impactful projects.
A professional and collaborative company culture.If you're ready to take on the next step in your career as a Data Engineer we encourage you to apply today

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.

Jobs

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.

Careers

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.

Jobs

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

🍪 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.