7 of 7 Deployment Automation Jobs in Berkshire

role will be Embedded within Vodafone's engineering teams to co-deliver reusable, production-ready platform components, Infrastructure as Code, CI/CD automation, observability, resilience and FinOps practices aligned to Vodafone's backlog and sprint cadence. The role will support secure, scalable and cost-effective cloud services while … reusable Azure platform templates and engineering patterns that can be adopted consistently across TaaZure workloads and environments. Implement and improve CI/CD pipelines, deployment automation, environment management and release practices for key platform services. Embed observability, monitoring, resilience, security and FinOps practices into platform components to improve ...

engineers, and developers, you will be responsible for developing, deploying, maintaining, and supporting scalable cloud-based applications on Microsoft Azure, with a focus on automation, reliability, performance optimisation, and large-scale data processing. Key Responsibilities Develop, deploy, and maintain applications using .NET Core, C#, Entity Framework, React, and Azure. ...

ready cloud capabilities that will underpin future digital services. Working alongside an established engineering team, you'll deliver reusable platform components, Infrastructure as Code, automation and engineering best practices while supporting the ongoing development of a modern enterprise cloud platform. If you're passionate about Azure platform engineering, automation … Azure-native tooling. Create reusable Azure platform templates and engineering patterns to support consistent platform adoption. Build and improve CI/CD pipelines, deployment automation and release processes. Implement observability, monitoring, logging, resilience and operational readiness across the platform. Embed FinOps principles, improving cloud cost visibility and optimisation. ...

product-led way of working that brings engineers, data specialists and business experts together to deliver meaningful outcomes at pace. We're scaling automation and AI from proof-of-concept into real, end-to-end change - improving customer journeys, reducing cost-to-serve, accelerating delivery, and building the digital … Experience Strong expertise in React Native and modern mobile application development. Proven experience delivering and supporting mobile applications through the full development lifecycle, including deployment to the Apple App Store and Google Play Store. Experience building robust automated testing strategies, including unit and integration testing. Strong understanding of mobile ...

Newbury. You will work on a high-profile platform initiative (TaaZure), co-delivering reusable, production-ready platform capabilities, Infrastructure as Code, CI/CD automation, and FinOps practices. We are offering flexibility on engagement - you can join either as a Permanent Employee with the consultancy … Delivery: Design and build production-ready IaC using Terraform and Terragrunt, creating modular, reusable Azure platform templates and landing zone patterns. CI/CD & Automation: Build and refine automated deployment pipelines, environment management, and release practices. Platform Quality: Embed observability (monitoring, logging, alerting), resilience, security, and FinOps principles ...

business stakeholders to turn ideas into practical solutions Technology environment includes: .NET and C# React, JavaScript and TypeScript Azure, Azure DevOps and AKS GitOps deployment practices PowerShell automation Python within emerging AI solutions What we're looking for Strong hands-on software engineering experience, ideally within SaaS ...

reliability and performance of high‐volume data systems. You'll partner closely with engineering, operational and commercial teams, taking ideas from hypothesis through to deployment, and ensuring models deliver real value once they're live. You'll join a collaborative team of data scientists, analysts and engineers, working … doing Developing and deploying machine‐learning models in production environments Working end‐to‐end across the data science lifecycle: problem definition, modelling, deployment and monitoring Analysing new and existing data sources to improve decision‐making and model performance Designing feedback loops that continuously improve outcomes and data quality Collaborating ...