26 to 50 of 641 GCP Jobs in the UK

About You Professional knowledge and experience Essential Proven experience in data engineering, data integration and data modelling Expertise with cloud platforms (e.g. AWS, Azure, GCP) Expertise with modern cloud data platforms (e.g. Microsoft Fabric, Databricks) Expertise with multiple data analytics tools (e.g. Power BI) Deep understanding of data wareho using

pipeline consuming other data products Basic qualifications: Extensive experience conducting Bankend Development using Python. Concurrency and Asyn exp Demonstrated experience using FastAPI Cloud Experience - GCP Essential SQL Docker Containerization Unit testing experience - TDD or Test Suit ML or AI experience would be desriable. Experience within Life Sceiences or Pharma Sector

roles, with at least 5 years in SRE, Observability, or DevOps functions.Proven track record implementing observability solutions in cloud-native environments (AWS, Azure, or GCP). Hands-on proficiency with observability tools such as Datadog, Grafana, Prometheus, OpenTelemetry. Strong knowledge of distributed systems, microservices, and container orchestration (Kubernetes, Docker).

other complex services) into production systems. Experience with containerization (Docker, Kubernetes) and deploying/managing services on a major cloud platform (AWS, GCP, or Azure). This is a permanent position with hybrid working of two days a week in the central London office and the rest WFH. The salary

other complex services) into production systems. Experience with containerization (Docker, Kubernetes) and deploying/managing services on a major cloud platform (AWS, GCP, or Azure). This is a permanent position with hybrid working of two days a week in the central London office and the rest WFH. The salary

/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

/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

passion for quality engineering will be essential. Experience with microservices, DDD, CQRS, advanced Kubernetes, or cloud platforms such as AWS, Azure or GCP will be an advantage, but not required. To be eligible for this role, you must hold or be able to obtain Developed Vetting (DV) clearance, including

level of ability/experience, you will have familiarity, competence or expertise in a subset of these areas: Cloud technologies: AWS primarily Azure and GCP beneficial Cyber security Vulnerability management (e.g. tenable) IDAM (e.g Azure AD, Keycloak) Virtualisation and Containerisation Containerisation (e.g. Docker, Podman) Container management (e.g. Kubernetes) Architectural styles

such as Maven or Gradle Nice to have Experience with React, JavaScript, HTML and CSS Familiarity with cloud platforms such as AWS, Azure or GCP Knowledge of CI/CD tools such as Jenkins or GitHub Actions Experience with microservices and database technologies like PostgreSQL or MySQL This

driven design (DDD). CQRS and Event Sourcing patterns * Kubernetes * Knowledge/Certification in Spring framework. * Experience in cloud technologies AWS/Azure/GCP Please apply for the job if you fit the above criteria.

cloud concepts. Experience contributing to solution design and familiarity with architectural patterns/frameworks. Proven delivery of serverless pipelines in Azure/AWS/GCP (Azure highly desirable). Experience building data transformation pipelines using SQL and NoSQL databases. Hands-on ownership of CI/CD (Jenkins/Azure DevOps

Java or Scala, plus experience with SQL and NoSQL databases Experience with Microsoft SQL Server and SSRS Familiarity with cloud platforms (AWS, Azure or GCP) and containerisation (Docker, Kubernetes) Strong understanding of CI/CD tooling and best practices The Benefits: Salary up to £77,000 Company bonus scheme Hybrid

engineering* Experience designing ML/AI solutions and working with common architecture patterns* Background in serverless data/ML pipelines (Azure preferred, AWS/GCP welcome)* Proficiency in SQL and NoSQL data stores* Broad understanding of machine learning methods (regression, tree-based models, clustering, deep learning, attention models, transformers, vector

APIs (REST, SOAP, XML/JSON) and web services. Understanding of version control systems (e.g., Git). Knowledge of cloud platforms (Azure, AWS, or GCP). Experience with Agile/Scrum development methodologies. Strong problem-solving skills and attention to detail. Desirable: Experience in transport, logistics, or supply chain systems

code quality and analysis tools (e.g., SonarQube). Background with job scheduling platforms such as Control-M. Experience with major cloud providers (Azure, AWS, GCP). Familiarity with VMware (vSphere) and storage area networks. Previous experience in financial services would be advantageous, though not a requirement. This is an exceptional

knowledge of Kubernetes, container orchestration, and microservices architecture. Expertise in Linux, networking, and security principles for containerized environments. Familiarity with cloud platforms (AWS, Azure, GCP) and hybrid cloud strategies. Experience with CI/CD tools (Jenkins, GitLab, Tekton) and DevOps practices. Ability to define technical standards and governance for container

About you: You have strong backend development experience with C# .Net You have a good knowledge of AWS (or other Cloud services, e.g. Azure. GCP) You have experience of building scalable, reliable and secure web applications and REST APIs using modern techniques You have experience of implementing frontend applications

PEGA rules engine. Nice to have: Active Security Clearance (SC) Proven experience working within Agile delivery frameworks Familiarity with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes) Strong understanding of DevOps practices, including CI/CD pipelines and automated testing tools for PEGA Background in regulated sectors such

PEGA rules engine. Nice to have: Active Security Clearance (SC) Proven experience working within Agile delivery frameworks Familiarity with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes) Strong understanding of DevOps practices, including CI/CD pipelines and automated testing tools for PEGA Background in regulated sectors such

PEGA rules engine. Nice to have: Active Security Clearance (SC) Proven experience working within Agile delivery frameworks Familiarity with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes) Strong understanding of DevOps practices, including CI/CD pipelines and automated testing tools for PEGA Background in regulated sectors such

Metropolis Open USD Python, TensorFlow, PyTorch GPU computing platforms (CUDA, cuDNN) Containerisation and orchestration tools (Docker, Kubernetes) Cloud platforms supporting AI workloads (AWS, Azure, GCP) Please send your CV to discuss in more detail InterQuest Group is acting as an employment agency for this vacancy. InterQuest Group is an equal

extract insights from complex and disparate data sets and communicate clearly with stakeholders Hands-on experience with cloud platforms such as AWS, Azure, or GCP Familiarity with traditional ETL tools (e.g., Informatica, Talend, Pentaho, DataStage) and data warehousing concepts Strong understanding of data security, compliance , and governance best practices Experience

/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

experience with OpenShift Virtualization and Kubernetes. 3. Proficiency in scripting languages (e.g., Bash, Python) for automation tasks. 4. Knowledge of cloud platforms (AWS, Azure, GCP) and hybrid cloud environments. 5. Familiarity with CI/CD tools (Jenkins, GitLab, ArgoCD, etc.). 6. Strong understanding of networking, storage, and virtualization concepts.