1 to 25 of 56 Contract Docker Jobs in London

Digital services , healthcare APIs, or standards such as FHIR, HL7, OpenAPI, or integration with NHS Spine (highly desirable). * Hands-on experience with Docker , Kubernetes , and containerized deployments. * Familiarity with CI/CD pipelines (Jenkins, GitLab CI, Azure DevOps, etc.). * Experience with cloud platforms such as AWS, Azure

model and query data effectively. Familiarity with distributed systems concepts such as event sourcing, resilience patterns, and asynchronous communication. Experience with containerised development (Docker) and deploying cloud-native applications (Azure, AWS, or GCP). Strong understanding of DevOps concepts: CI/CD pipelines, automated testing, infrastructure-as-code patterns. Proficiency

Digital services , healthcare APIs, or standards such as FHIR, HL7, OpenAPI, or integration with NHS Spine (highly desirable). Hands-on experience with Docker , Kubernetes , and containerized deployments. Familiarity with CI/CD pipelines (Jenkins, GitLab CI, Azure DevOps, etc.). Experience with cloud platforms such as AWS, Azure

Java and .NET. Oracle SQL PL to support existing services. Infrastructure/DevOps technologies including AWS, Azure, SQL server, Postgres, GitHub, Azure DevOps, Linux, docker and Kubernetes Continuous. deployment, supported by automated testing and monitoring. Software written using Test Driven Development practices, with developers writing their automated tests before creating

Secure AI Framework (SAIF). Experience with engineering Security Solutions for Container Technology and micro services - Kubernetes (GKE, EKS or AKS), ECS or Fargate, Docker, ECR, GCR, etc. Experience with engineering Security Solutions for Development, Security and Operations (DevSecOps). Experience with Cloud Security Posture Management tools - C3M, Prisma Cloud

Java and .NET. Oracle SQL PL to support existing services. Infrastructure/DevOps technologies including AWS, Azure, SQL server, Postgres, GitHub, Azure DevOps, Linux, docker and Kubernetes Continuous. deployment, supported by automated testing and monitoring. Software written using Test Driven Development practices, with developers writing their automated tests before creating

Python and Bash. Knowledge of Linux-based systems and source control tools such as Git or SVN. Experience with containerisation technologies such as Docker and Kubernetes. Strong analytical, documentation, and problem-solving skills. Excellent communication skills and ability to work collaboratively in multi-disciplinary teams. Desirable ISTQB certification or equivalent.

computing Familiarity with time-series, market data, transactional data or risk metrics Nice to Have Power BI dataset preparation OneLake, Azure Data Lake, Kubernetes, Docker Knowledge of financial regulations (GDPR, SOX) Details Location: London (office-based) Type: Contract Duration: 6 months Start: ASAP Rate: Market rates

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 as Banking, Insurance

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 as Banking, Insurance

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 as Banking, Insurance

multi-disciplinary teams Desirable Skills for the AWS Data Engineer: Experience with Databricks , Kafka , or Kinesis for real-time data streaming Knowledge of containerisation (Docker, ECS) and modern orchestration tools such as Airflow Familiarity with machine learning model deployment pipelines or data lakehouse architectures Data Engineer, AWS Data Engineer

Spring framework or equivalent. Knowledge of software design patterns and when to apply them Excellent knowledge of development processes. Experience of containerisation using Docker or Kubernetes Experience of Continuous Integration (CI) and Continuous Delivery (CD) A passion for delivering quality code, by use of TDD and setting high software quality

Spring framework or equivalent. Knowledge of software design patterns and when to apply them Excellent knowledge of development processes. Experience of containerisation using Docker or Kubernetes Experience of Continuous Integration (CI) and Continuous Delivery (CD) A passion for delivering quality code, by use of TDD and setting high software quality

Spring framework or equivalent. Knowledge of software design patterns and when to apply them Excellent knowledge of development processes. Experience of containerisation using Docker or Kubernetes Experience of Continuous Integration (CI) and Continuous Delivery (CD) A passion for delivering quality code, by use of TDD and setting high software quality

Solid programming skills (Python/C#,/.NET) Experience with Azure DevOps, CI/CD pipelines, and GitHub Actions. Knowledge of containerization (tools ie Docker) and orchestration (ie Kubernetes on Azure). Good awareness of Data & AI - understanding of ML lifecycle, MLOps, and Responsible AI. Strong problem-solving and analytical

controls within cloud environments Ability to produce high-quality documentation and support governance standards Technical Skills Infrastructure as Code (IaC): Terraform, Bicep Containerisation: Kubernetes, Docker CI/CD Pipelines: GitLab CI, Jenkins Scripting & Automation: Python, PowerShell If your looking for a new challenge and this sounds like

databases (FAISS, Pinecone, Weaviate) and graph technologies (Neo4j). Familiarity with observability tools and AI evaluation frameworks. Strong grasp of containerization and cloud deployment (Docker, AWS, Azure). Tools & Platforms GitHub Copilot, ChatGPT/GPT-4, Claude for AI-assisted development. LangChain, LlamaIndex for RAG implementations. SonarQube for code security

databases (FAISS, Pinecone, Weaviate) and graph technologies (Neo4j). Familiarity with observability tools and AI evaluation frameworks. Strong grasp of containerization and cloud deployment (Docker, AWS, Azure). Tools & Platforms GitHub Copilot, ChatGPT/GPT-4, Claude for AI-assisted development. LangChain, LlamaIndex for RAG implementations. SonarQube for code security

Azure Data Engineer certification preferred -eg- Azure Data Engineer Associate. Advantageous skills: Azure Event Hubs, Kafka, data visualisation tools, Power BI, Tableau, Azure DevOps, Docker, Kubernetes, Jenkins.

front-end best practices. Experience with Git, CI/CD pipelines, and automated deployment workflows. Exposure to cloud platforms (AWS preferred) and containerisation (Docker/Kubernetes) is beneficial. Strong debugging skills and the ability to work independently in a fast-paced environment. If this role sounds of interest - apply today

LLaMA, Cohere Frameworks: LangChain, LlamaIndex, Haystack Tools: GitHub Copilot, Cursor, PromptLayer, Weights & Biases Cloud: Azure ML, AWS SageMaker, Google Vertex AI, Databricks Infra: Python, Docker, Kubernetes, SQL, PyTorch

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

Skills and Experience Banking experience is essential Strong software engineering background with expert Python Hands-on experience with GitLab CI/CD Extensive Docker containerisation & runtime experience Strong understanding of AWS SageMaker deployments Experience building developer environments for ML/quant/data-intensive workflows Knowledge of monitoring, logging, reporting

AutoGen, CrewAI Tools: GitHub Copilot, Cursor, LangSmith, LangFuse, Weights & Biases, MLflow, Humanloop Cloud: Azure ML, AWS SageMaker, Google Vertex AI, Databricks, Modal Infra: Python, Docker, Kubernetes, SQL/NoSQL, PyTorch, FastAPI, Redis