Senior Data Engineer (Big Data/ Hadoop/ Spark) (Banking)

Hays Technology
London
2 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Your new company

Working for a renowned financial services organisation

Your new role

We're looking for a Senior Data Engineer to design and deliver scalable on prem, high‑quality data solutions for low/ high-level data platforms that power analytical and business insights. This is a hands‑on role suited to someone with strong data engineering and big data expertise, ideally gained within financial services. Joining leading commodities, metals, trading, and exchange group, you will support a strategic metals initiative focused on reducing on‑prem platform costs and modernising legacy ETL processes.

You'll help design and build a new on‑prem data platform aligned to the metals strategy while developing and maintaining scalable data pipelines and analytics infrastructure. Using Hadoop, Big Data, and Spark technologies, you will ensure data quality through automated validation, monitoring, and testing. You will also enable seamless integration across data warehouses and data lakes, contributing to a robust, scalable, and resilient enterprise data ecosystem.

What you'll need to succeed

Vast Data Engineering expertise with Big Data technologies.
Experience designing and building on‑prem data platforms, from high‑level architecture to detailed technical design.
Hands‑on experience configuring multi‑node Hadoop clusters, including resource management, security, and performance tuning.
Strong Big Data engineering background using Apache Airflow, Spark, dbt, Kafka, and Hadoop ecosystem tools.
Knowledge of RDBMS systems (PostgreSQL, SQL Server) and familiarity with NoSQL/distributed databases such as MongoDB.
Proven delivery of streaming pipelines and real‑time data processing solutions.
Improved job efficiency and reduced runtimes through Apache Spark optimisation and development.
Some experience with containerisation (Docker, Kubernetes) and CI/CD pipelines.
Delivered streaming pipelines and real‑time data processing solutions.
Experience replacing legacy ETL tools (e.g., Informatica) with modern data engineering pipelines and platform builds.
Proven background working within financial services environments.
What you'll get in return
Flexible working options available.

What you need to do now
If you're interested in this role, click 'apply now' to forward an up-to-date copy of your CV, or call us now.

Hays Specialist Recruitment Limited acts as an employment agency for permanent recruitment and employment business for the supply of temporary workers. By applying for this job you accept the T&C's, Privacy Policy and Disclaimers which can be found at (url removed)

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.

Products

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.

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.

🍪 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.