676 to 700 of 2,439 Docker Jobs in England

development of machine learning models and/or deep learning to solve complex science and engineering problems Experience with MLOps tools and practices, including Airflow, MLflow, and containerization (e.g., Docker) A passion for gaining insight into real-world datasets and clearly communicating through data visualization techniques Interest in material discovery, computer vision, handling big data and optimisation techniques Highly effective More ❯

development of machine learning models and/or deep learning to solve complex science and engineering problems Experience with MLOps tools and practices, including Airflow, MLflow, and containerization (e.g., Docker) A passion for gaining insight into real-world datasets and clearly communicating through data visualization techniques Interest in material discovery, computer vision, handling big data and optimisation techniques Highly effective More ❯

data architecture, with proven experience across SQL, NoSQL, and graph databases such as Neo4j or Amazon Neptune. Strong understanding of distributed systems, API design, and modern deployment practices using Docker, Kubernetes, and CI/CD pipelines. Comfort working in cloud-based environments (AWS preferred), including data connectivity and infrastructure-as-code principles. Experience integrating LLMs, RAG pipelines, or vector databases More ❯

data architecture, with proven experience across SQL, NoSQL, and graph databases such as Neo4j or Amazon Neptune. Strong understanding of distributed systems, API design, and modern deployment practices using Docker, Kubernetes, and CI/CD pipelines. Comfort working in cloud-based environments (AWS preferred), including data connectivity and infrastructure-as-code principles. Experience integrating LLMs, RAG pipelines, or vector databases More ❯

development of machine learning models and/or deep learning to solve complex science and engineering problems Experience with MLOps tools and practices, including Airflow, MLflow, and containerization (e.g., Docker) A passion for gaining insight into real-world datasets and clearly communicating through data visualization techniques Interest in material discovery, computer vision, handling big data and optimisation techniques Highly effective More ❯

in an engineering role, with a track record of delivering innovative technology solutions. Strong programming skills in Python, C#, or similar languages. Experience with CI/CD pipelines, containerisation (Docker/Kubernetes) Familiarity with cloud platforms (Azure, AWS, or GCP) Understanding of data engineering principles, including ETL, data pipelines, and database management. Working knowledge of ML/AI concepts and More ❯

Snowflake, Databricks, BigQuery, Redshift). Experience with time-series data, and/or implementing data pipelines from major financial market data vendors (Bloomberg, Refinitiv, Factset....) SDLC and DevOps: Git, Docker, Jenkins/TeamCity, monitoring, testing, agile practices. Passionate about code quality, data integrity, and building scalable and robust systems. Ability to communicate clearly with technical and non-technical colleagues. This More ❯

Snowflake, Databricks, BigQuery, Redshift). Experience with time-series data, and/or implementing data pipelines from major financial market data vendors (Bloomberg, Refinitiv, Factset....) SDLC and DevOps: Git, Docker, Jenkins/TeamCity, monitoring, testing, agile practices. Passionate about code quality, data integrity, and building scalable and robust systems. Ability to communicate clearly with technical and non-technical colleagues. This More ❯

data architecture, with proven experience across SQL, NoSQL, and graph databases such as Neo4j or Amazon Neptune. Strong understanding of distributed systems, API design, and modern deployment practices using Docker, Kubernetes, and CI/CD pipelines. Comfort working in cloud-based environments (AWS preferred), including data connectivity and infrastructure-as-code principles. Experience integrating LLMs, RAG pipelines, or vector databases More ❯

data architecture, with proven experience across SQL, NoSQL, and graph databases such as Neo4j or Amazon Neptune. Strong understanding of distributed systems, API design, and modern deployment practices using Docker, Kubernetes, and CI/CD pipelines. Comfort working in cloud-based environments (AWS preferred), including data connectivity and infrastructure-as-code principles. Experience integrating LLMs, RAG pipelines, or vector databases More ❯

data architecture, with proven experience across SQL, NoSQL, and graph databases such as Neo4j or Amazon Neptune. Strong understanding of distributed systems, API design, and modern deployment practices using Docker, Kubernetes, and CI/CD pipelines. Comfort working in cloud-based environments (AWS preferred), including data connectivity and infrastructure-as-code principles. Experience integrating LLMs, RAG pipelines, or vector databases More ❯

adaptability Leadership experience with strong communication skills Structured approach to quantitative challenges Comfort working in a dynamic startup environment Qualifications Microsoft Azure experience, particularly R integration Application containerization knowledge (Docker, etc.) Familiarity with Python, JavaScript, C++, bash, or other languages Web application development experience (React, .NET) Background in data security and IP protection workflows Knowledge of environmental sustainability concepts (carbon More ❯

Snowflake, Databricks, BigQuery, Redshift). Experience with time-series data, and/or implementing data pipelines from major financial market data vendors (Bloomberg, Refinitiv, Factset....) SDLC and DevOps: Git, Docker, Jenkins/TeamCity, monitoring, testing, agile practices. Passionate about code quality, data integrity, and building scalable and robust systems. Ability to communicate clearly with technical and non-technical colleagues. This More ❯

Snowflake, Databricks, BigQuery, Redshift). Experience with time-series data, and/or implementing data pipelines from major financial market data vendors (Bloomberg, Refinitiv, Factset....) SDLC and DevOps: Git, Docker, Jenkins/TeamCity, monitoring, testing, agile practices. Passionate about code quality, data integrity, and building scalable and robust systems. Ability to communicate clearly with technical and non-technical colleagues. This More ❯

Snowflake, Databricks, BigQuery, Redshift). Experience with time-series data, and/or implementing data pipelines from major financial market data vendors (Bloomberg, Refinitiv, Factset....) SDLC and DevOps: Git, Docker, Jenkins/TeamCity, monitoring, testing, agile practices. Passionate about code quality, data integrity, and building scalable and robust systems. Ability to communicate clearly with technical and non-technical colleagues. This More ❯

experience. Strong hands-on experience with AWS/Azure and SaaS platforms . Solid Linux & Windows system administration experience. Proficiency in Infrastructure as Code : Terraform and Ansible. Experience with Docker and Kubernetes . A strong focus on automation-first DevOps practices. Extremely strong written and verbal skills What We Offer Our people are important to us. As well as a More ❯

practices. Desirable: Relevant certifications are highly desirable, such as: VMware Certified Professional (VCP) Microsoft Certified: Azure Administrator/Solutions Expert AWS Certified Solutions Architect CompTIA Security+ Knowledge of Kubernetes, Docker, and container orchestration in virtualised/cloud environments. Strong communication skills and ability to work effectively in cross-functional teams. Why Join DXC Technology? Work on enterprise-scale virtualisation and More ❯

to translate prototypes into reliable, maintainable ML applications. Identify opportunities to develop new ML solutions in partnership with Data Science teams. Platform & Tooling Automate and standardise ML infrastructure using Docker, Kubernetes, and Terraform. Support and develop monitoring dashboards for key ML and AI services. Ensure cloud-native, secure, and cost-efficient deployments in AWS environments. Contribute to the development of More ❯

to translate prototypes into reliable, maintainable ML applications. Identify opportunities to develop new ML solutions in partnership with Data Science teams. Platform & Tooling Automate and standardise ML infrastructure using Docker, Kubernetes, and Terraform. Support and develop monitoring dashboards for key ML and AI services. Ensure cloud-native, secure, and cost-efficient deployments in AWS environments. Contribute to the development of More ❯

modern toolchains to our customers to rapidly visualise software applications Skills/Experience Experience, designing, building and operating modern applications Hands-on expertise with a tech stack consisting of docker, containerisation, Terraform, Azure, IaaS, PaaS, microservices and API management Proficiency in modern software development practices, including Agile methodologies, DevOps, and CI/CD pipelines Expert understanding of cloud technologies, including More ❯

to translate prototypes into reliable, maintainable ML applications. Identify opportunities to develop new ML solutions in partnership with Data Science teams. Platform & Tooling Automate and standardise ML infrastructure using Docker, Kubernetes, and Terraform. Support and develop monitoring dashboards for key ML and AI services. Ensure cloud-native, secure, and cost-efficient deployments in AWS environments. Contribute to the development of More ❯

to translate prototypes into reliable, maintainable ML applications. Identify opportunities to develop new ML solutions in partnership with Data Science teams. Platform & Tooling Automate and standardise ML infrastructure using Docker, Kubernetes, and Terraform. Support and develop monitoring dashboards for key ML and AI services. Ensure cloud-native, secure, and cost-efficient deployments in AWS environments. Contribute to the development of More ❯

to translate prototypes into reliable, maintainable ML applications. Identify opportunities to develop new ML solutions in partnership with Data Science teams. Platform & Tooling Automate and standardise ML infrastructure using Docker, Kubernetes, and Terraform. Support and develop monitoring dashboards for key ML and AI services. Ensure cloud-native, secure, and cost-efficient deployments in AWS environments. Contribute to the development of More ❯

infrastructure provisioning, configuration, and deployment within a highly secure environment. Collaborate as part of a multi-disciplined Agile/Scrum team. Key Technologies Cloud & Infrastructure : AWS CloudFormation, Amazon ECS, Docker, Kubernetes Automation & CI/CD : CI/CD automation (ideally DroneCI), Git (GitHub or GitLab), Ansible Scripting & Administration : Advanced Linux administration and scripting (e.g., Bash) Security : Strong knowledge of security More ❯

strong problem-solving skills Other highly desirable, but not essential skills are: Azure certifications, such as Azure Administrator, Azure Developer, or Azure DevOps Engineer Experience with containerization and orchestration (Docker, Kubernetes) Familiarity with programming languages such as C# Knowledge of Configuration as Code tools (e.g., Puppet, Ansible) At WTW, we believe difference makes us stronger. We want our workforce to More ❯