1 to 25 of 81 GCP Jobs in the East Midlands

tooling: Cursor, Windsurf, GitHub copilot • AI powered platform development: Lovable, Replit, Bolt • APIs & Microservices: RESTful APIs, GraphQL, microservice architectures • Cloud & DevOps: AWS, Azure, or GCP; Docker; CI/CD pipelines • Data Integration: Products integrating ML/AI models, databases, BI tools • UI/UX Awareness: Collaborate on interfaces, data visualisation ...

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 ...

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 ...

techniques (e.g., classification, NLP, GenAI, RAG, prompt engineering), data pipelines, APIs, and microservices. Hands-on experience with cloud platforms (Azure preferred; AWS or GCP also valued) and MLOps tools (e.g., MLflow, Azure ML, Databricks, SageMaker or Vertex) plus observability practices. Familiarity with higher education processes and integrations across ...

techniques (e.g., classification, NLP, GenAI, RAG, prompt engineering), data pipelines, APIs, and microservices. Hands-on experience with cloud platforms (Azure preferred; AWS or GCP also valued) and MLOps tools (e.g., MLflow, Azure ML, Databricks, SageMaker or Vertex) plus observability practices. Familiarity with higher education processes and integrations across ...

techniques (e.g., classification, NLP, GenAI, RAG, prompt engineering), data pipelines, APIs, and microservices. Hands-on experience with cloud platforms (Azure preferred; AWS or GCP also valued) and MLOps tools (e.g., MLflow, Azure ML, Databricks, SageMaker or Vertex) plus observability practices. Familiarity with higher education processes and integrations across ...

techniques (e.g., classification, NLP, GenAI, RAG, prompt engineering), data pipelines, APIs, and microservices. Hands-on experience with cloud platforms (Azure preferred; AWS or GCP also valued) and MLOps tools (e.g., MLflow, Azure ML, Databricks, SageMaker or Vertex) plus observability practices. Familiarity with higher education processes and integrations across ...

techniques (e.g., classification, NLP, GenAI, RAG, prompt engineering), data pipelines, APIs, and microservices. Hands-on experience with cloud platforms (Azure preferred; AWS or GCP also valued) and MLOps tools (e.g., MLflow, Azure ML, Databricks, SageMaker or Vertex) plus observability practices. Familiarity with higher education processes and integrations across ...

architecture Data modelling, cataloguing, and associated governance Data lakes, distributed storage Metadata management Cloud & Platform Architecture Proficient in AWS, but familiarity with Azure/GCP also useful Strong understanding of cloud computing principles (and ideally the AWS core services that deliver them) IaC literacy (ideally Terraform) Software Architecture Microservices, monoliths ...

architecture Data modelling, cataloguing, and associated governance Data lakes, distributed storage Metadata management Cloud & Platform Architecture Proficient in AWS, but familiarity with Azure/GCP also useful Strong understanding of cloud computing principles (and ideally the AWS core services that deliver them) IaC literacy (ideally Terraform) Software Architecture Microservices, monoliths ...

architecture Data modelling, cataloguing, and associated governance Data lakes, distributed storage Metadata management Cloud & Platform Architecture Proficient in AWS, but familiarity with Azure/GCP also useful Strong understanding of cloud computing principles (and ideally the AWS core services that deliver them) IaC literacy (ideally Terraform) Software Architecture Microservices, monoliths ...

architecture Data modelling, cataloguing, and associated governance Data lakes, distributed storage Metadata management Cloud & Platform Architecture Proficient in AWS, but familiarity with Azure/GCP also useful Strong understanding of cloud computing principles (and ideally the AWS core services that deliver them) IaC literacy (ideally Terraform) Software Architecture Microservices, monoliths ...

architecture Data modelling, cataloguing, and associated governance Data lakes, distributed storage Metadata management Cloud & Platform Architecture Proficient in AWS, but familiarity with Azure/GCP also useful Strong understanding of cloud computing principles (and ideally the AWS core services that deliver them) IaC literacy (ideally Terraform) Software Architecture Microservices, monoliths ...

will work across cutting‐edge platforms including Payment Networks, Digital Banking, Emerging Payments, and highly scalable data and analytics environments built on Google Cloud Platform, Data Lakes and Power BI. This role involves modern engineering, integration, testing, and hands‐on development within a high‐impact digital landscape. Key Responsibilities Code ...

will work across cutting‐edge platforms including Payment Networks, Digital Banking, Emerging Payments, and highly scalable data and analytics environments built on Google Cloud Platform, Data Lakes and Power BI. This role involves modern engineering, integration, testing, and hands‐on development within a high‐impact digital landscape. Key Responsibilities Code ...

will work across cutting‐edge platforms including Payment Networks, Digital Banking, Emerging Payments, and highly scalable data and analytics environments built on Google Cloud Platform, Data Lakes and Power BI. This role involves modern engineering, integration, testing, and hands‐on development within a high‐impact digital landscape. Key Responsibilities Code ...

will work across cutting‐edge platforms including Payment Networks, Digital Banking, Emerging Payments, and highly scalable data and analytics environments built on Google Cloud Platform, Data Lakes and Power BI. This role involves modern engineering, integration, testing, and hands‐on development within a high‐impact digital landscape. Key Responsibilities Code ...