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Transform Healthcare with Cutting-Edge Tech! 🚀Position: Data Engineer (Python/Databricks) Location: Remote Salary: Up to £80,000 + BenefitsAre you driven by a passion for health tech and innovation? Do you dream of revolutionizing clinical research through advanced technology? If so, we have an incredible opportunity for you!Join our trailblazing team as a Data Engineer and play a pivotal role in building...
Data Engineer - 4/5 Month contract - ÂŁ180PD - 8 hour working day - Bex-Hill- on-sea, Hastings ****Location: - Bex Hill, HastingsDuration: - 4/5 monthsStart Date: ASAP startDay Rate: ÂŁ180PD Based on 8 hour working dayCerts - ECS/CSCSJob Responsibilities: Cabling works, Cable Pulling, Taking instructions off lead engineerExperience: As aboveTools / PPE - Basic Hand tools, Full PPE (5 point...
We need a Data Engineer that is passionate about data and able to use various methods to transform raw data into useful data systems. The primary role of the Data Engineer is to combine expertise, programming skill, data science and business intelligence to extract meaningful insights from the data.this is a great opportunity has arisen for a Data Engineer, to...
Prestigious opportunity with a Market Leading Global Retail organisation for a Data Engineer to join our success story in Blackburn. Following a period of significant growth, we are expanding our team to further drive the business forward.You will be responsible for:-Designing, building and maintaining scalable data pipelines using Python, MS SQL server and robust data pipelines to transform and store...
Shields Talent are working exclusively with a charity based in Edinburgh that are looking for a Data Engineer to join their team on a 12-month fixed term contract.In this role the Data Engineer will work with the data team to develop a new data warehouse solution with the required data pipelines to support the delivery of their strategy. Supporting the...
Data Engineer required by our market leading, award winning, professional services organisation based in Yeovil.The successful Data Engineer, you'll play a vital role in designing, building, and maintaining sophisticated data pipelines and ensuring the integrity of our clients extensive customer data. Your work will support data-driven decision-making across the business, helping to drive forward key customer insights and analytics.In this...
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Data engineering has become an indispensable pillar of the modern technology ecosystem. As companies gather massive troves of data—often measured in petabytes—the importance of robust, scalable data pipelines cannot be overstated. From ingestion and storage to transformation and analysis, data engineers stand at the forefront of delivering reliable data for analytics, machine learning, and critical business decisions. Simultaneously, the field of Artificial Intelligence (AI) has undergone a revolution, transitioning from niche research projects to a foundational tool for everything from predictive maintenance and fraud detection to customer experience personalisation. Yet as AI models grow in complexity—think large language models with hundreds of billions of parameters—the data volumes and computational needs escalate dramatically. The industry finds itself at an inflection point: traditional computing systems may eventually hit performance ceilings, even when scaled horizontally with thousands of nodes. Enter quantum computing, a nascent yet rapidly progressing technology that leverages quantum mechanics to tackle certain computational tasks exponentially faster than classical machines. While quantum computing is still maturing, its potential to supercharge AI workflows—often referred to as quantum-enhanced AI—has piqued the curiosity of data engineers and enterprises alike. This synergy could solve some of the biggest headaches in data engineering: accelerating data transformations, enabling more efficient analytics, and even facilitating entirely new kinds of modelling once believed to be intractable. In this article, we explore: How data engineering has evolved to support AI’s insatiable appetite for high-quality, well-structured data. The fundamentals of quantum computing and why it may transform the data engineering landscape. Potential real-world applications for quantum-enhanced AI in data engineering—from data ingestion to machine learning pipeline optimisation. Emerging career paths and skill sets needed to thrive in a future where data, AI, and quantum computing intersect. Challenges, ethical considerations, and forward-looking perspectives on how this convergence might shape the data engineering domain. If you work in data engineering, are curious about quantum computing, or simply want to stay on the cutting edge of technology, read on. The next frontier of data-driven innovation may well be quantum-powered.
Data. It’s the critical lifeblood of every forward-thinking organisation, fueling everything from strategic decision-making to real-time analytics. As data volumes skyrocket and technologies mature, the UK has distinguished itself as a frontrunner in data innovation. A robust venture capital scene, government-backed initiatives, and a wealth of academic talent have created fertile ground for data-centric start-ups across the country. In this Q3 2025 Investment Tracker, we’ll delve into the newly funded UK start-ups shaping the future of data engineering. More importantly, we’ll explore the rich job opportunities that have emerged alongside these funding announcements. From building scalable ETL (Extract, Transform, Load) pipelines to architecting data warehouses and implementing advanced data governance frameworks, data engineers, architects, and analysts have an incredible array of roles to pursue. If you’re eager to elevate your career in data engineering, read on for insights into the most dynamic start-ups, their fresh capital injections, and the skill sets they’re hungry for.
Data is increasingly the lifeblood of businesses, driving everything from product development to customer experience. At the centre of this revolution are data engineers—professionals responsible for building robust data pipelines, architecting scalable storage solutions, and preparing data for analytics and machine learning. If you’re looking to land a role in this exciting and high-demand field, a strong CV is only part of the puzzle. You also need a compelling data engineering portfolio that shows you can roll up your sleeves and deliver real-world results. In this guide, we’ll cover: Why a data engineering portfolio is crucial for standing out in the job market. Choosing the right projects for your target data engineering roles. Real GitHub examples that demonstrate best practices in data pipeline creation, cloud deployments, and more. Actionable project ideas you can start right now, from building ETL pipelines to implementing real-time streaming solutions. Best practices for structuring your GitHub repositories and showcasing your work effectively. By the end, you’ll know exactly how to build and present a portfolio that resonates with hiring managers—and when you’re ready to take the next step, don’t forget to upload your CV on DataEngineeringJobs.co.uk. Our platform connects top data engineering talent with companies that need your skills, ensuring your portfolio gets the attention it deserves.
The world of data engineering has rapidly emerged as a critical pillar for businesses, enabling them to extract insights from vast amounts of information and power data-driven decision-making. From building scalable ETL pipelines to designing real-time streaming infrastructures and cloud data warehouses, data engineers are in high demand across every industry—from tech giants to healthcare providers to financial institutions. If you’re seeking a data engineering role, you may already know that interviews can be rigorous, spanning software development, database design, distributed systems, and cloud computing. Many organisations need engineers who can handle both traditional batch processing and cutting-edge real-time analytics frameworks, all while keeping data secure, consistent, and optimised. In this guide, we’ll explore 30 real coding & system-design questions that often come up in data engineering interviews. From classic coding challenges to architecture-focused scenarios, these questions will help you gauge your readiness and build confidence before stepping into that interview room. If you’re actively searching for new data engineering opportunities in the UK, www.dataengineeringjobs.co.uk is a fantastic resource. It features a wide range of vacancies—from junior data engineering positions to senior-level cloud architecture roles. Let’s dive in so you can approach your next interview with insight and poise.
How to Secure a Compensation Package That Reflects Your Value in the UK’s Fast-Growing Data Ecosystem Introduction Data engineering has quickly become the backbone of modern business operations. Whether powering analytics platforms, migrating data to the cloud, or building pipelines for machine learning, data engineers enable organisations to extract meaningful insights from vast datasets. With companies across every sector looking to harness data for competitive advantage, mid‑senior data engineers are in especially high demand—and that spells opportunity for you to negotiate a compelling compensation package. Yet for many professionals, negotiations around a job offer still focus primarily on salary, leading them to overlook valuable components such as equity, performance bonuses, and perks that can collectively add significant value to your overall deal. In the world of data engineering, it’s not uncommon to see advanced compensation packages involving shares, annual or quarterly bonuses, and a range of benefits that support both your technical growth and work-life balance. This guide aims to be your comprehensive manual for negotiating a data engineering job offer in the UK. We’ll cover why negotiation isn’t just about your monthly paycheck, explore how equity works in data-centric organisations, break down different bonus structures, and highlight perks that matter most for mid‑senior professionals. By the end, you’ll have the knowledge—and the confidence—to land a package that fully reflects your critical role in unlocking the power of data.
Data has become one of the most valuable assets in today’s digital age, enabling organisations to make data-driven decisions, optimise processes, and deliver improved services. Nowhere is the potential impact of robust data engineering practices more significant than in the UK public sector. From the National Health Service (NHS) to the Government Digital Service (GDS) and the Ministry of Defence (MOD), large volumes of data are continually generated and processed, creating a rising demand for data engineering jobs. In this blog post, we’ll explore why data engineering is so essential for public sector bodies, the range of roles available, the skills and qualifications needed to excel, and how you can secure a highly rewarding career in this domain. Whether you’re a seasoned data professional or just starting out in tech, read on to discover how to make a meaningful impact through data engineering jobs in the UK’s public sector.
