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 EngineerI am working with a data driven Microsoft partnered consultancy who are looking for a Databricks Data Engineer to join their growing team. You will have the opportunity to work with some of the latest Microsoft technologies with a focus on projects on Databricks implementations.You will join a team at the centre of a number of data-driven projects where...
Data EngineerI am working with a data driven Microsoft partnered consultancy who are looking for a Databricks Data Engineer to join their growing team. You will have the opportunity to work with some of the latest Microsoft technologies with a focus on projects on Databricks implementations.You will join a team at the centre of a number of data-driven projects where...
Data Engineer Position based in Horsham or WatfordWe are seeking a highly skilled and motivated Data Engineer – Power BI to lead the design, development, and implementation of Business Intelligence (BI) solutions. This role involves engaging with stakeholders across the organisation to deliver insightful, data-driven reports that support strategic decision-making.Location: Astral House, Imperial Way, Watford WD24 4WW or Albion House,...
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...
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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.
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