Senior Cloud Infrastructure DevOps Engineer

Bedford
3 weeks ago
Create job alert

Role: Senior Azure Cloud Infrastructure/DevOps Engineer

Location: Office in Bedfordshire

Working Arrangements: Hybrid working policy of 2 days in the office per week

Salary: up to £100k plus great benefits, including enhanced pension and 35 hour working week

You’ve been looking for a great company that’s financially stable, with a lot of interesting work to do, with modern tech, that you can throw yourself into and use your skills to their fullest.

You want to be around people physically some of the week to collaborate and to feel a part of something bigger than yourself.

If this describes you, read on, this could be the one for you.

A great little company, of around 10 people, in Bedfordshire are building out a new engineering team and you could be a part of it. They are a Microsoft house, so their cloud infrastructure tech is strongly centered around Azure, and their services.

At a glance, here’s what you’ll need experience with:

  • Strong knowledge of Azure App Services, Azure Functions, Azure FrontDoor, Azure ADB2C, Azure SQL and Azure API Management

  • Experience of Azure Monitor, Log Analytics and Application Insights

  • Proficiency with Azure Backup and Site Recovering

  • Skills in Azure Cost Management and billing

  • Knowledge of Azure DevOps pipelines

    I am looking for someone who is the full package- not only a Cloud Infrastructure/ DevOps Engineer, skilled in the above technologies, who loves to create efficient, elegant, and well-documented technical solutions, but also who is a great person to be around- a real team player who is naturally curious, takes the initiative, and wants to pitch in wherever they can whilst maintaining and advocating for best practice and who adheres to the Well-Architected Framework.

    They are, as a company, about to undertake a huge migration project to bring their technical estate back in-house, from a 3rd party. This will span across all areas of the business and will be keeping everyone busy for a long while! Don’t worry though, once this is completed, there will be lots of other projects, products, and solutions to be made, so you’ll not be bored here.

    As you can imagine, big projects like this need short feedback loops and lots of collaboration, which is often easier to do when everyone is in the same place, so a hybrid working policy of 2 days per week in the office is there to facilitate that.

    This is great role for you to really use all your skills on some fab projects, in a fun environment with friendly, talented people. If you’re looking to make your mark at a company, shape how things are done, and have a voice – this is the place for you.

    If this sounds right up your street, get in touch now or apply for immediate consideration!

    We welcome diverse applicants and are dedicated to treating all applicants with dignity and respect, regardless of background

Related Jobs

View all jobs

Senior Java Developer

Senior Java Developer

Senior Data Solutions Designer

Senior Data Solutions Designer

Full Stack Developer

Senior Data Engineer_London_Hybrid

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Quantum-Enhanced AI in Data Engineering: Reshaping the Big Data Pipeline

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 Engineering Jobs at Newly Funded UK Start-ups: Q3 2025 Investment Tracker

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.

Portfolio Projects That Get You Hired for Data Engineering Jobs (With Real GitHub Examples)

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.