1 to 25 of 198 GCP Jobs in the North of England

proficiency in one or more programming languages (e.g., Python, Java, JavaScript) and experience with software architecture patterns. Experience with cloud platforms (e.g., AWS, Azure, GCP) and infrastructure as code. Familiarity with CI/CD pipelines, automated testing, and modern software development practices. Knowledge of technologies such as microservices, containerisation (Docker ...

proficiency in one or more programming languages (e.g., Python, Java, JavaScript) and experience with software architecture patterns. Experience with cloud platforms (e.g., AWS, Azure, GCP) and infrastructure as code. Familiarity with CI/CD pipelines, automated testing, and modern software development practices. Knowledge of technologies such as microservices, containerisation (Docker ...

proficiency in one or more programming languages (e.g., Python, Java, JavaScript) and experience with software architecture patterns. Experience with cloud platforms (e.g., AWS, Azure, GCP) and infrastructure as code. Familiarity with CI/CD pipelines, automated testing, and modern software development practices. Knowledge of technologies such as microservices, containerisation (Docker ...

multiple programming languages such as Python, JavaScript, or similar. Extensive experience writing well-tested code. Good knowledge of cloud platforms (e.g., AWS, Azure, GCP) and infrastructure as code Experience with CI/CD pipelines and automated testing frameworks. Experience with various architecture patterns eg microservices and event-driven. Experience with ...

multiple programming languages such as Python, JavaScript, or similar. Extensive experience writing well-tested code. Good knowledge of cloud platforms (e.g., AWS, Azure, GCP) and infrastructure as code Experience with CI/CD pipelines and automated testing frameworks. Experience with various architecture patterns eg microservices and event-driven. Experience with ...

multiple programming languages such as Python, JavaScript, or similar. Extensive experience writing well-tested code. Good knowledge of cloud platforms (e.g., AWS, Azure, GCP) and infrastructure as code Experience with CI/CD pipelines and automated testing frameworks. Experience with various architecture patterns eg microservices and event-driven. Experience with ...

reliable and scalable back-end systems with an object-oriented language. Cloud-native technologies: Experience in architecting and deploying in cloud platforms (e.g., AWS, GCP or Azure), an understanding of containerisation (e.g., Docker), infrastructure-as-code software (e.g., Terraform), and observability platforms (e.g., Datadog or Grafana). Strong ownership mindset ...

reliable and scalable back-end systems with an object-oriented language. Cloud-native technologies: Experience in architecting and deploying in cloud platforms (e.g., AWS, GCP or Azure), an understanding of containerisation (e.g., Docker), infrastructure-as-code software (e.g., Terraform), and observability platforms (e.g., Datadog or Grafana). Strong ownership mindset ...

reliable and scalable back-end systems with an object-oriented language. Cloud-native technologies: Experience in architecting and deploying in cloud platforms (e.g., AWS, GCP or Azure), an understanding of containerisation (e.g., Docker), infrastructure-as-code software (e.g., Terraform), and observability platforms (e.g., Datadog or Grafana). Strong ownership mindset ...

reliable and scalable back-end systems with an object-oriented language. Cloud-native technologies: Experience in architecting and deploying in cloud platforms (e.g., AWS, GCP or Azure), an understanding of containerisation (e.g., Docker), infrastructure-as-code software (e.g., Terraform), and observability platforms (e.g., Datadog or Grafana). Strong ownership mindset ...

reliable and scalable back-end systems with an object-oriented language. Cloud-native technologies: Experience in architecting and deploying in cloud platforms (e.g., AWS, GCP or Azure), an understanding of containerisation (e.g., Docker), infrastructure-as-code software (e.g., Terraform), and observability platforms (e.g., Datadog or Grafana). Strong ownership mindset ...

reliable and scalable back-end systems with an object-oriented language. Cloud-native technologies: Experience in architecting and deploying in cloud platforms (e.g., AWS, GCP or Azure), an understanding of containerisation (e.g., Docker), infrastructure-as-code software (e.g., Terraform), and observability platforms (e.g., Datadog or Grafana). Strong ownership mindset ...

reliable and scalable back-end systems with an object-oriented language. Cloud-native technologies: Experience in architecting and deploying in cloud platforms (e.g., AWS, GCP or Azure), an understanding of containerisation (e.g., Docker), infrastructure-as-code software (e.g., Terraform), and observability platforms (e.g., Datadog or Grafana). Strong ownership mindset ...

patterns, and secure coding practices Experience working with SQL/NoSQL databases (PostgreSQL, Oracle) Nice‐to‐Have Skills Experience with cloud platforms (AWS, Azure, GCP) Containerization knowledge (Docker, Kubernetes) UI development in PEGA or frameworks like Angular/React Familiarity with DevOps tools (Jenkins, Git, SonarQube, CI/CD pipelines ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data pipelines, APIs ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data pipelines, APIs ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data pipelines, APIs ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data pipelines, APIs ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data pipelines, APIs ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data pipelines, APIs ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data pipelines, APIs ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data pipelines, APIs ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data pipelines, APIs ...

/TypeScript, Java, C# Frameworks: Vue/Angular/React/Node/Next, Spring/Spring Boot, .NET/ASP.NET Cloud platforms: AWS, GCP, Azure CI/CD:Jenkins, GitHub Actions, Azure DevOps IaC: Terraform, CloudFormation, Azure Bicep Pragmatic and safe usage of AI through the SDLC (e.g. using ...

best practices Required Skills & Experience Proven experience architecting distributed systems (microservices, REST APIs, cloud-native solutions) Strong hands-on expertise with AWS, Azure, or GCP , including migration strategies Solid software engineering background (eg Java, Python) with Agile delivery experience Financial services domain experience, ideally within payments, cards, or digital channels ...