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Junior to Mid-Level Data Engineer – Financial Services | Strong Kafka/Streaming Focus- London/Hybrid (2 days per week) – Up to £70K (DOE)My client, an innovative and rapidly expanding Financial Services organisation, is seeking a Junior to Mid-Level Data Engineer to join their highly technical data team. This is a unique opportunity to be part of a forward thinking company where...
Data Engineer - Remote - £65,000My client, a growing, high-impact consultancy is looking for a hands-on Data Engineer to join its expert team. Working across a mix of exciting, high-profile clients in various different sectors.You will join their expanding team to build robust platforms and create intelligent solutions.If you thrive in fast-paced environments, enjoy variety in your work, and want...
Data EngineerI am looking for a Data Engineer to join an established retailer as they look to migrate to Microsoft Fabric. They are looking to integrate a number of their data systems into one fully-scalable solution and create a brand-new data warehouse that will enable data to be readily available for reporting.The business have office locations around the UK, however...
Data EngineerI am looking for a Data Engineer to join an established retailer as they look to migrate to Microsoft Fabric. They are looking to integrate a number of their data systems into one fully-scalable solution and create a brand-new data warehouse that will enable data to be readily available for reporting.The business have office locations around the UK, however...
Dublin 2 Location, 2days/week on siteOpportunity to play an active role in setting our client's Data Strategy€70k-€80k/year + 15% bonus + benefitsYou’ll work alongside a small but dedicated Data Team, reporting to the Data Manager, and collaborate with one other Data Engineer and a Systems Analyst.This is a hybrid role offering the chance to contribute to both operational and strategic...
Data Engineer required by high growth travel firm in Blackpool.Salary: £45,000 - £50,000 plus pension, 25 days holidays, opportunity to purchase moreLocation: Blackpool, Lancashire – Office Based 5 days a weekEnvironment: Innovative, energetic and collaborative culture with regular training and development opportunities.Looking for a skilled and results-driven Data & Analysis Engineer with hands-on experience in Google BigQuery and Power BI...
Advance your Data Engineering career with expert advice, practical job search tips, and insightful industry guides.
Trying to land your next data engineering job? Discover the 10 most common mistakes UK candidates make—plus practical fixes, expert tips and curated resources to help you secure your ideal role. Introduction From real-time analytics teams in London fintechs to modern data platforms powering Cambridge health-tech, demand for data engineering talent across the UK has never been higher. Yet recruiters on DataEngineeringJobs.co.uk still reject the majority of CVs long before interview—often for small, avoidable errors. We analysed recent vacancies, interviewed in-house hiring managers and mined our most-read resources. The result is a definitive list of the 10 costliest application mistakes, each paired with an actionable fix and a helpful link for deeper learning. Bookmark this checklist before you press Apply.
Discover ten of the strongest UK universities for Data Engineering degrees in 2025. Compare entry requirements, course content, research strength and industry links to choose the right programme for you. Data is the fuel of the digital economy, and turning raw records into reliable, analysis-ready information is the job of the data engineer. From building lake-house architectures to orchestrating near-real-time pipelines, demand for these skills is soaring across finance, retail, health-tech and government. The UK boasts several universities recognised internationally for large-scale data systems and scalable computing. Below we profile ten institutions whose undergraduate or postgraduate pathways major on data engineering. Tables shift each year, but these universities have a consistent record of excellence in teaching, research and industry collaboration.
Learn how to craft the perfect cover letter for data science jobs with this proven 4-paragraph structure. Ideal for entry-level candidates, career switchers, and professionals looking to advance in the data science sector. When applying for a data science job, your cover letter is an essential part of your application. The data science field is highly competitive, with many candidates vying for the same roles. Your cover letter allows you to showcase your technical expertise, analytical skills, and your ability to apply data to solve real-world problems. It’s the perfect opportunity to demonstrate your passion for data and your understanding of how it can drive meaningful insights for an organisation. Whether you're new to data science, making a career switch, or looking to advance your skills, this article will guide you through a proven four-paragraph structure to craft a compelling cover letter. We’ll provide sample lines and tips to help you stand out in the highly competitive data science job market.
Learn how to craft the perfect cover letter for data engineering jobs with this proven 4-paragraph structure. Ideal for entry-level candidates, career switchers, and professionals looking to advance in the data engineering sector. When applying for a data engineering job, your cover letter is a vital component of your application. The data engineering field is critical for organisations that rely on big data to make informed decisions, and a well-crafted cover letter will allow you to demonstrate your expertise in data management, data architecture, and data pipeline construction. Writing a cover letter for a data engineering role can seem challenging, but with the right structure, it becomes much easier to highlight your strengths. Whether you're just entering the field, transitioning from another role, or seeking to advance your career in data engineering, this article will walk you through a proven four-paragraph structure. We’ll provide sample lines and practical tips to help you create a cover letter that stands out from the competition in the data engineering job market.
Introduction Every modern mission—whether directing humanitarian aid, mapping enemy positions, or forecasting equipment failures—runs on data. The same is true for British business. The UK Big Data & Analytics market is forecast to hit £36 billion by 2026 (IDC), and Gartner reports that data engineering vacancies grew 38 % in 2024, outpacing data‑science demand for the first time. Organisations urgently need professionals who can collect, clean, and pipeline petabytes of information—exactly the logistical, analytical, and security‑minded tasks veterans perform in theatre. If you’ve routed tactical sensor feeds, managed supply‑chain databases, or written Python scripts to crunch signal logs, you already think like a data engineer. This guide maps military skills to civilian data‑engineering roles, spotlights Ministry of Defence (MoD) transition funding, and shows you how to secure a rewarding second career building the pipelines that power AI and business intelligence. Quick Win: Browse our live listings for Data Pipeline Engineer roles to see which employers are hiring this week.
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.
