Data Engineer

Noir
Newcastle upon Tyne
5 months ago
Create job alert

Data Engineer - FinTech - Newcastle

(Tech stack: Data Engineer, SQL, Python, AWS, Git, Airflow, Data Pipelines, Data Platforms, Programmer, Developer, Architect, Data Engineer)

Our client is a trailblazer in the FinTech space, known for delivering innovative technology solutions to global financial markets. They are expanding their engineering capability in Newcastle and are looking for a talented Data Engineer to join their team. This role will focus on building and optimising systems that make complex datasets accessible, reliable, and valuable for the business.

As a Data Engineer, you will take responsibility for the development of high-quality pipelines that process and manage large volumes of data from a range of external and internal sources. You'll play a key role in enhancing and maintaining their central data platform, ensuring the smooth delivery of information that supports investment decision-making. Working closely with stakeholders across the business, you'll help shape how data is accessed, tested, and leveraged to maximise value.

The successful candidate will bring:

  • 3-6 years of relevant experience working as a Data Engineer (or in a closely related role).
  • A 2:1 or above in Computer Science (or related field), ideally from a Russell Group university.
  • Direct experience in the hedge fund sector (essential).
  • Strong ability to design and build data pipelines that integrate mul...

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

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.

New Data Engineering Employers to Watch in 2026: UK and Global Companies Driving the Data Revolution

Data engineering is at the heart of the digital economy, transforming raw data into actionable insights, powering analytics, AI systems, and cloud infrastructure. As the UK and global markets continue to invest heavily in data platforms, pipelines, and real-time analytics, demand for skilled data engineers is growing rapidly. For professionals exploring opportunities on www.DataEngineeringJobs.co.uk , the critical question is: which companies are expanding, hiring, and shaping the future of data-driven business? This article highlights new data engineering employers to watch in 2026, including UK startups, scale-ups, and international firms expanding in the UK.

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

If you’re aiming for a career in data engineering, it can feel like you’re staring at a never-ending list of tools and technologies — SQL, Python, Spark, Kafka, Airflow, dbt, Snowflake, Redshift, Terraform, Kubernetes, and the list goes on. Scroll job boards and LinkedIn, and it’s easy to conclude that unless you have experience with every modern tool in the data stack, you won’t even get a callback. Here’s the honest truth most data engineering hiring managers will quietly agree with: 👉 They don’t hire you because you know every tool — they hire you because you can solve real data problems with the tools you know. Tools matter. But only in service of outcomes. Jobs are won by candidates who know why a technology is used, when to use it, and how to explain their decisions. So how many data engineering tools do you actually need to know to get a job? For most job seekers, the answer is far fewer than you think — but you do need them in the right combination and order. This article breaks down what employers really expect, which tools are core, which are role-specific, and how to focus your learning so you look capable and employable rather than overwhelmed.

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

If you’re applying for data engineering jobs in the UK, the first thing to understand is this: Hiring managers don’t read every word of your CV. They scan it. They look for signals of relevance, credibility, delivery and collaboration — and if they don’t see the right signals quickly, your application may never get a second look. In data engineering, hiring managers are especially focused on whether you can build and operate reliable, scalable data systems, handle real-world data challenges and work effectively with analytics, BI, data science and engineering teams. This guide breaks down exactly what they look at first in your application — and how to shape your CV, portfolio and cover letter so you stand out.