Data Engineer

Cardiff
4 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer - Cardiff / Hybrid - £45,000 - £50,000 + benefits

Yolk Recruitment are excited to be working with a global technology business that's continuing to expand its data capability and invest in modern cloud solutions. Known for their collaborative culture and commitment to innovation, they're offering an excellent opportunity for a Data Engineer to make a real impact.

We're looking for a Data Engineer to help design, build, and maintain scalable data pipelines and systems that power analytics and business intelligence across the organisation. You'll play a key role in ensuring data is accurate, accessible, and high-quality - driving data-led decision making at every level.

What you'll be doing:

Design, build, and maintain scalable data pipelines and ETL processes to support analytics and operations.
Develop and optimise data models and storage solutions for performance and reliability.
Ensure data quality, integrity, and security throughout the data lifecycle.
Collaborate with data scientists, analysts, and engineers to deliver effective data solutions.
Implement and maintain infrastructure on AWS, Azure, or GCP.
Monitor and troubleshoot data workflows to ensure availability and minimal downtime.
Automate data ingestion, transformation, and validation processes.
Stay up to date with emerging technologies and recommend system improvements.The skills you'll need:

Strong proficiency in SQL and experience with relational databases.
Hands-on experience building data pipelines and ETL processes.
Proficiency in Python.
Experience with cloud platforms (AWS, Azure, or GCP).
Knowledge of data modelling, warehousing, and optimisation.
Familiarity with big data frameworks (e.g. Apache Spark, Hadoop).
Understanding of data governance, security, and compliance best practices.
Strong problem-solving skills and experience working in agile environments.Desirable:

Experience with Docker/Kubernetes, streaming data (Kafka/Kinesis), Terraform, CI/CD pipelines, and NoSQL databases.

Company Benefits:

Enhanced Parental Leave
Generous annual leave
Healthcare Plan
Annual Giving Day - an extra day to give back to yourself or your community
Cycle-to-work Scheme
Pension scheme with employer contributions
Life Assurance - 3x base salary
Rewards Programme - access to discounts and cashback
LinkedIn Learning Licence for upskilling & developmentReady to Apply?

Please apply with your latest CV.

Know someone who'd be great for this role? We offer a referral scheme-just get in touch!

Note: We do our best to respond to every application, but due to volume, we can't always guarantee it. If you haven't heard back within 7 days, unfortunately, you haven't been successful this time. Keep an eye on our site for new opportunities

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.

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.

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.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.