DevOps Engineer

Bridgend
9 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer

Data Engineer

Data Engineer

Data Engineer - Minerva - Contract - SC Clearance

Java Developer with SQL & GIT

Data Engineer

DevOps Engineer
South Wales (Hybrid - up to 3 days per week in office)
Up to £55,000

CPS Group are working with a a global, innovative organisation with a long-standing presence in the specialty insurance and risk management industry. They provide expert solutions and tailored services to complex client needs across a wide range of sectors. The company places a strong emphasis on stability, professional development, and investing in cutting-edge technologies to deliver excellence.

As a DevOps Engineer, you will play a key role in supporting and improving the software delivery lifecycle across international business applications. Working within a cross-functional team, you will enhance development processes, optimise release procedures, and collaborate on infrastructure and deployment automation projects.

Key Responsibilities

Install, deploy and configure .NET and web applications.

Manage and deploy changes across environments (DEV, TEST, PROD) using structured release processes.

Administer Microsoft SQL Server environments and deploy SQL scripts.

Maintain and manage virtualised server environments (e.g., VMWare).

Support deployment and configuration of enterprise applications such as BizTalk, MS Dynamics, CRM, and Pega.

Develop and maintain deployment documentation and procedures.

Perform system monitoring, log reviews, and ensure backup completion.

Manage Active Directory permissions and service accounts.

Contribute to disaster recovery planning and testing.

Identify and implement automation opportunities.

Create and maintain CI/CD pipelines using modern DevOps tools.

Promote a collaborative DevOps culture and attend monthly DevOps forums.

Essential Skills & Experience

Proven experience in application deployment and configuration.

Background in software development, testing, or support.

Strong troubleshooting skills for environment and application issues.

Experience with:

Windows Server & SQL Server Management Studio

IIS, Apache Tomcat

Virtualisation platforms (e.g., VMWare)

CI/CD pipelines (Azure DevOps, GitHub Actions, AWS CI/CD, etc.)

Automation tools (Terraform, Ansible, PowerShell)

Containerisation tools (Docker, Kubernetes, Minikube)

Strong stakeholder management and communication skills.

Desirable Experience

Previous experience working in the insurance or financial services sector.

Exposure to third-party software systems such as Salesforce, MS Dynamics, Guidewire, BizTalk, Pega, or Verisk products.

Experience leading automation initiatives or application support in a multi-platform environment.

Interested? Contact: Zach Bennett - CPS Group

By applying to this advert you are giving CPS Group (UK) Ltd authority to hold and process your data for this specific role and any other roles we may deem suitable to you over time. We will not pass your data to any third party without your verbal or written permission to do so. All incoming and outgoing calls are recorded for training and compliance purposes. CPS Group (UK) Ltd is acting as an Employment Agency in relation to this vacancy. Our new privacy policy can be found here (url removed)

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.

Careers

How Many Data Engineering Tools Do You Need to Know to Get a Data Engineering Job?

If you’re aiming for a career in data engineering, it can feel like you’re staring at a never-ending list of tools and technologies — SQL, Python, Spark, Kafka, Airflow, dbt, Snowflake, Redshift, Terraform, Kubernetes, and the list goes on. Scroll job boards and LinkedIn, and it’s easy to conclude that unless you have experience with every modern tool in the data stack, you won’t even get a callback. Here’s the honest truth most data engineering hiring managers will quietly agree with: 👉 They don’t hire you because you know every tool — they hire you because you can solve real data problems with the tools you know. Tools matter. But only in service of outcomes. Jobs are won by candidates who know why a technology is used, when to use it, and how to explain their decisions. So how many data engineering tools do you actually need to know to get a job? For most job seekers, the answer is far fewer than you think — but you do need them in the right combination and order. This article breaks down what employers really expect, which tools are core, which are role-specific, and how to focus your learning so you look capable and employable rather than overwhelmed.

Jobs

What Hiring Managers Look for First in Data Engineering Job Applications (UK Guide)

If you’re applying for data engineering jobs in the UK, the first thing to understand is this: Hiring managers don’t read every word of your CV. They scan it. They look for signals of relevance, credibility, delivery and collaboration — and if they don’t see the right signals quickly, your application may never get a second look. In data engineering, hiring managers are especially focused on whether you can build and operate reliable, scalable data systems, handle real-world data challenges and work effectively with analytics, BI, data science and engineering teams. This guide breaks down exactly what they look at first in your application — and how to shape your CV, portfolio and cover letter so you stand out.

Education

The Skills Gap in Data Engineering Jobs: What Universities Aren’t Teaching

Data engineering has quietly become one of the most critical roles in the modern technology stack. While data science and AI often receive the spotlight, data engineers are the professionals who design, build and maintain the systems that make data usable at scale. Across the UK, demand for data engineers continues to rise. Organisations in finance, retail, healthcare, government, media and technology all report difficulty hiring candidates with the right skills. Salaries remain strong, and experienced professionals are in short supply. Yet despite this demand, many graduates with degrees in computer science, data science or related disciplines struggle to secure data engineering roles. The reason is not academic ability. It is a persistent skills gap between university education and real-world data engineering work. This article explores that gap in depth: what universities teach well, what they consistently miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data engineering.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.