At a Glance
- Tasks: Support and automate digital infrastructure for IoT and connected products.
- Company: Join a leading FTSE100 engineering group with a collaborative culture.
- Benefits: Hybrid work, competitive salary, and opportunities for professional growth.
- Other info: Exciting career path into MLOps and machine learning platform engineering.
- Why this job: Make an impact in IoT and DevOps while developing your skills in a dynamic environment.
- Qualifications: Degree in Computer Science or related field; experience in DevOps and cloud operations.
The predicted salary is between 63000 - 77000 £ per year.
Location: Redruth, Cornwall UK
Location Type: Hybrid (2/3)
Watson-Marlow Fluid Technology Solutions is part of Spirax Group, a FTSE100 and FTSE4Good multi-national industrial engineering Group with expertise in the control and management of steam, electric thermal solutions, peristaltic pumping and associated fluid technologies. When you join us, you will be integrated into a cooperative and encouraging team, participate in challenging yet critical work, and experience ongoing growth opportunities to help you achieve your full potential.
Job Summary: The DevOps & IoT Platform Engineer is responsible for supporting the build, operation, automation, and reliability of the digital infrastructure that underpins Watson-Marlow’s connected products and industrial IoT capabilities. The role will initially focus on DevOps, cloud platform operations, IoT data flows, deployment automation, environment management, monitoring, and secure integration between connected devices, cloud services, data platforms, and engineering teams. As the capability matures, the role will provide a clear development path into MLOps and ML platform engineering, supporting model deployment, model lifecycle controls, ML pipeline automation, and governed promotion of machine learning solutions from development into production.
Key Responsibilities:
- DevOps, cloud operations and platform reliability
- Build, maintain and improve automation for cloud and IoT platform services that support connected products.
- Develop and maintain CI/CD pipelines, deployment workflows, environment controls and repeatable release processes using tools such as GitHub, Azure DevOps and related platform tooling.
- Help maintain Azure-based development, test, QA and production environments used by digital, IoT, data and ML platforms.
- Contribute to secure platform configuration, access control, secrets management, monitoring and operational governance.
- Monitor platform health, investigate operational issues and contribute to improving reliability, supportability and repeatability across digital product environments.
IoT data flows, data pipelines and operational support
- Support reliable device-to-cloud data flows from connected products, gateways, cloud services and downstream data platforms.
- Work with telemetry, time-series and industrial IoT data sources, helping to ensure data is available, structured and usable for engineering, product and analytics teams.
- Support operational data pipelines that provide reliable data for engineering analytics, product insights, connected services and machine learning use cases.
- Assist with troubleshooting data ingestion, connectivity, data quality and integration issues across the connected-products ecosystem.
- Document deployment steps, support processes and platform knowledge to improve maintainability and reduce reliance on manual intervention.
Collaboration, security and controlled platform change
- Work with IT, cyber security, software, firmware and supplier teams to support service availability, incident resolution and controlled platform change.
- Contribute to data validation, monitoring, transformation and handover between operational platforms and analytical environments.
- Proactively identify opportunities to simplify, automate and strengthen digital platform delivery.
Growth into MLOps and ML platform engineering
- Develop capability in MLOps practices such as experiment tracking, model packaging, model registry, model promotion and governed deployment workflows.
- Support AI developers with repeatable workflows that move ML code, configuration and artefacts through controlled development, test, QA and production stages.
- Contribute to the longer-term development of the ML platform, including quality gates, lifecycle controls, operational monitoring and supportability.
Skills/Experience:
- Qualifications: Bachelor’s or Master’s degree in Computer Science, Data Engineering, Data Science, Software Engineering, or a related discipline (or equivalent experience).
- Experience in DevOps, platform engineering, cloud operations, software deployment, or infrastructure automation.
- Experience with CI/CD pipelines, source control, branching strategies, pull requests, and release workflows using GitHub, Azure DevOps, or similar tools.
- Exposure to Azure cloud services and operational practices, including monitoring, access control, environment management, and secure configuration.
- Experience working with IoT, telemetry, time-series, connected-product, or industrial data platforms.
- Proficiency in scripting or automation using Python, PowerShell, Bash, or equivalent tooling.
- Understanding of data pipelines, APIs, integration patterns, and operational troubleshooting.
- Strong problem-solving skills with the ability to work across software, data, cloud, and connected-product teams.
- Experience with Azure IoT services, Azure Data Explorer, Databricks, containerisation, APIs, or cloud-native application deployment.
- Experience with infrastructure as code, automated testing, observability, logging, or platform monitoring.
- Aware of MLOps concepts such as MLflow, model registry, model promotion, model monitoring, and governed deployment pipelines.
- Exposure to machine learning workflows or data science environments, with an interest in developing into ML platform engineering.
- Experience working with industrial equipment, embedded systems, firmware teams, or device-to-cloud architectures.
DevOps & IoT Platform Engineer in Redruth employer: Watson-Marlow Fluid Technology Solutions
Watson-Marlow Fluid Technology Solutions is an excellent employer, offering a dynamic hybrid working environment that fosters collaboration and innovation. With a strong focus on employee growth, the company provides comprehensive support through an inclusion plan, alongside competitive salaries, flexible working arrangements, and a generous holiday allowance, making it an attractive place for those seeking meaningful and rewarding employment.
Contact Details:
Watson-Marlow Fluid Technology Solutions Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land DevOps & IoT Platform Engineer in Redruth
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We think you need these skills to ace DevOps & IoT Platform Engineer in Redruth
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Watson-Marlow Fluid Technology Solutions.
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How to prepare for a job interview at Watson-Marlow Fluid Technology Solutions
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Watson-Marlow Fluid Technology Solutions uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
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While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
