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Senior Azure Cloud & DevOps Engineer

Newcastle Upon Tyne

£60,000- £70,000 per year depending on experience

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5 Oct 2026

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Job Description

A key purpose of the role is to help transition existing computational and data-processing workflows from traditional or manually managed environments into scalable, reliable and automated cloud-native solutions, increasing processing capacity and throughput as business demand grows. This includes containerising existing applications and processing workflows, deploying and orchestrating them through Kubernetes where appropriate, and ensuring that cloud resources are appropriately configured for performance, scalability, resilience and cost.

The role will take ownership of the technical implementation of workloads within Azure, including the configuration and optimisation of AKS clusters, containers, compute resources, storage, networking, monitoring and deployment pipelines.

The Senior Azure Cloud & DevOps Engineer will work as part of the Software Development team, while collaborating closely with Origin's Geospatial, InSAR, Engineering and R&D teams to understand existing processing workflows and determine how they can be efficiently deployed and operated within the cloud. As these cloud automation initiatives mature, the role will increasingly contribute as a senior engineering resource across the wider Software Development team's products, integrations and automation activities.

The role requires both strong cloud infrastructure knowledge and hands-on software engineering capability. The successful candidate will be expected to understand existing applications and processing scripts, including Python-based workflows developed by specialist teams, troubleshoot them where necessary and adapt or improve them to operate reliably within containerised and distributed cloud environments.

Particular emphasis will be placed on automation, observability, performance optimisation and operational reliability, ensuring that large or computationally intensive workloads can be executed efficiently and that failures can be identified and diagnosed quickly.

The role will contribute to establishing Origin's longer-term cloud architecture, DevOps standards and deployment practices, while supporting the broader development of secure, scalable and maintainable software solutions across the organisation.

Information Security Responsibilities

As part of our commitment to ISO 27001, you will contribute to our information security responsibilities and our integrated management system. This will include but is not limited to:

Complying with all information security policies and procedures.
Reporting security incidents or suspicious activity promptly.
Following access control and data handling requirements.
Participating in mandatory security awareness training.

Protecting organisational assets and information.

Roles & Responsibilities

Design, implement and maintain Microsoft Azure cloud infrastructure supporting Origin’s computational and data-processing workflows.
Lead the deployment and operation of containerised workloads using Azure Kubernetes Service (AKS) and Docker.
Migrate existing local, server-based and manually managed processing workflows into scalable and reliable Azure environments, designing and optimising cloud data movement and storage strategies for large processing workloads.
Develop, maintain and optimise software applications, scripts and processing workflows for cloud-based execution.
Benchmark and profile computationally intensive workflows to identify CPU, memory, storage I/O, network and application-level bottlenecks, and use the results to determine appropriate Azure VM sizes, parallelisation strategies and scaling configurations.
Design and configure Kubernetes workloads, including pods, jobs, services, storage, scheduling, and CPU/memory resource allocation.
Implement parallelisation, workload distribution, job scheduling and autoscaling to improve processing performance and cloud resource utilisation, with appropriate resource isolation so that multiple concurrent processing workloads do not adversely affect one another.
Design and implement workflow orchestration for multi-stage processing pipelines, including dependency management, conditional execution, stage-level retries, checkpointing and recovery mechanisms.
Implement comprehensive monitoring, logging and alerting to provide clear visibility of application, container and infrastructure performance and failures.
Implement and maintain monitoring technologies such as Azure Monitor, Log Analytics, Container Insights, Application Insights, Prometheus and Grafana, where appropriate.
Design and maintain CI/CD pipelines using tools such as Azure DevOps and/or GitHub Actions to automate testing, containerisation and deployment, and support automated and repeatable approaches to cloud infrastructure provisioning and configuration.
Support secure cloud networking, identity and access management, secrets management, and appropriate separation between development, test and production environments.
Work closely with Software Development, Geospatial, InSAR, Engineering and R&D teams to translate technical and processing requirements into suitable cloud architectures and to containerise and integrate satellite, geospatial/GIS and other processing components into scalable, automated and reliable end-to-end cloud workflows.
Optimise large-scale and computationally intensive workflows for performance, scalability, reliability and Azure cost efficiency.
Troubleshoot and lead root-cause investigation across software applications, containers, Kubernetes, networking, storage, cloud infrastructure and deployment pipelines.
Support wider software development activities across Origin’s products, platforms and internal tools, contributing to software design, development, testing, integration, code review and technical problem-solving where required.
Contribute to the ongoing development and improvement of Origin Orbit®, Origin No Dig® and other software, automation and R&D initiatives.
Maintain technical documentation, operational procedures and cloud engineering standards, while supporting knowledge transfer and clearly communicating technical progress, risks and recommendations to stakeholders.

HSEQ Responsibilities

Stop work where activities are considered unsafe.
Promote and enforce health, safety, environmental and quality standards within engineering activities.
Ensure compliance with ISO 9001, ISO 14001 and ISO 45001 (Occupational Health & Safety) management systems.
Support internal and external audit requirements where applicable.
Ensure product and service compliance with applicable legislation and regulatory requirements.
Be aware of and manage risks relating to People, Environment, Assets and Reputation (PEAR).
Participate in required HSEQ training and support adherence to relevant HSEQ requirements within the team.

Competence Requirements

Degree in Software Engineering, Computer Science, Information Technology, Cloud Computing or a related discipline is desirable, or equivalent professional experience.
Significant professional experience in Software Engineering, Cloud Engineering, DevOps, Platform Engineering or a similar technical role, with strong hands-on software development experience in production environments.
Strong hands-on experience with Microsoft Azure is essential.
Strong practical experience designing, deploying and operating workloads using Azure Kubernetes Service (AKS) and Kubernetes is essential.
Strong understanding of Kubernetes concepts including pods, deployments, jobs, services, namespaces, resource requests and limits, persistent volumes, configuration and workload scheduling.
Strong experience with Docker and containerisation, including building, troubleshooting and optimising container images.
Strong software development experience in one or more modern programming languages is essential, together with sound software engineering principles and the ability to understand, troubleshoot, modify and optimise existing applications and processing workflows.
Experience with Python, particularly for data-processing, scientific or automation workloads, would be advantageous.

Strong understanding of cloud architecture and distributed processing principles, including scalability, resilience, availability and performance.

Experience configuring and optimising compute-intensive workloads, including management of CPU, memory, storage and parallel processing requirements.

Strong experience with CI/CD pipelines and deployment automation, using Azure DevOps, GitHub Actions or equivalent technologies. Experience with automated and repeatable cloud infrastructure provisioning and configuration, including an understanding of Infrastructure as Code principles, would be advantageous.
Strong understanding of Git and collaborative version-control workflows.
Strong Linux knowledge and experience working with command-line tools and scripting using Bash and/or PowerShell.
Good understanding of cloud security principles.
Understanding of DevOps and DevSecOps principles, including automation, environment management, deployment automation, monitoring and operational ownership.
Ability to design cloud infrastructure and software solutions that are repeatable, maintainable, observable and resilient.
Ability to document cloud architecture, deployment processes and operational procedures clearly.

Experience working with large datasets and high-volume storage or data-transfer requirements.

Experience with workflow orchestration, job queues or distributed processing frameworks would be advantageous.

Experience with AWS or another major cloud platform would be advantageous, as would knowledge of PostgreSQL/PostGIS or other spatial databases.

General Capabilities

Degree in Software Engineering, Computer Science, Information Technology, Cloud Computing or a related discipline is desirable, or equivalent professional experience.
Significant professional experience in Software Engineering, Cloud Engineering, DevOps, Platform Engineering or a similar technical role, with strong hands-on software development experience in production environments.
Strong hands-on experience with Microsoft Azure is essential.
Strong practical experience designing, deploying and operating workloads using Azure Kubernetes Service (AKS) and Kubernetes is essential.
Strong understanding of Kubernetes concepts including pods, deployments, jobs, services, namespaces, resource requests and limits, persistent volumes, configuration and workload scheduling.
Strong experience with Docker and containerisation, including building, troubleshooting and optimising container images.
Strong software development experience in one or more modern programming languages is essential, together with sound software engineering principles and the ability to understand, troubleshoot, modify and optimise existing applications and processing workflows.
Experience with Python, particularly for data-processing, scientific or automation workloads, would be advantageous.

Strong understanding of cloud architecture and distributed processing principles, including scalability, resilience, availability and performance.

Experience configuring and optimising compute-intensive workloads, including management of CPU, memory, storage and parallel processing requirements.

Strong experience with CI/CD pipelines and deployment automation, using Azure DevOps, GitHub Actions or equivalent technologies. Experience with automated and repeatable cloud infrastructure provisioning and configuration, including an understanding of Infrastructure as Code principles, would be advantageous.
Strong understanding of Git and collaborative version-control workflows.
Strong Linux knowledge and experience working with command-line tools and scripting using Bash and/or PowerShell.
Good understanding of cloud security principles.
Understanding of DevOps and DevSecOps principles, including automation, environment management, deployment automation, monitoring and operational ownership.
Ability to design cloud infrastructure and software solutions that are repeatable, maintainable, observable and resilient.
Ability to document cloud architecture, deployment processes and operational procedures clearly.
Experience working with large datasets and high-volume storage or data-transfer requirements.
Experience with workflow orchestration, job queues or distributed processing frameworks would be advantageous.
Experience with AWS or another major cloud platform would be advantageous, as would knowledge of PostgreSQL/PostGIS or other spatial databases.