Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Operational Technology Engineer

Plymouth
6 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer

Lead Data Engineer Technology (Product, Engineering, Design) · London ·

Senior Data Analyst Technology (Product, Engineering, Design) · London ·

2026 Graduate Digital and Data Analyst, Infrastructure Delivery

Data Analytics Engineer

Senior Data Engineer ( SC Cleared/ SC Eligible )

As the Operational Technology Engineer you will report to the Operational Technology lead, you will manage the ongoing development and maintenance of the (OT) systems at the Plymouth manufacturing site.

Main responsibilities will include:

  • Conduct OT asset inventory discovery, management, and asset risk assessments.

  • Support network architecture changes in line with OT security programme policy changes.

  • Drive plant initiatives and project specification, risk assessments and policy adherence activities.

  • Implement protocols to ensure accurate OT device recognition and management ensuring to follow OT policy and guidelines.

  • Lead Cyber-risk awareness and security policy training, to enabling the business to maximise system usage benefits while integrating cybersecurity measures to protect data integrity and security.

  • Complete third-party vendor risk assessments, critical patch implementation, application whitelist testing and implementation. Diagnosing root causes of system failures and define and undertake appropriate corrective actions.

  • Co-ordinating OT process/system change management and organise testing or approval of changes. Implementing all change requests using the approved methodology, ensuring the appropriate level of authorisation and documentation.

  • Engage in ongoing educational and self-development activities as required by the role.

  • Provide business and regulatory data reports and relevant information to meet customer needs utilising available Business Intelligence technologies.

  • Work with other business teams to ensure correct usage of the systems.

    About you:

  • First class or upper second-class honours degree from a recognised university specialising in engineering disciplines or relevant experience with HND / HNC.

  • Several years’ experience in a related environment, ideally medical device manufacture or pharmaceutical.

  • Experience and working knowledge of change control processes within a regulated medical device manufacturing environment.

  • Demonstrated experience with networking, software, and control systems in a related environment.

  • Broad demonstrable experience of Enterprise IT systems, networking protocols and hardware with a keen interest in the OT environment and the interface between the IT and Control Systems Engineering disciplines.

  • Demonstrated achievement with software and control systems in a related environment.

  • Ability to read and interpret electrical drawings, network schematics (physical and logical) and floor plans.

  • Ability to process, combine, and analyse large disperse datasets to produce meaningful insights.

  • An understanding of with Allen Bradley, Siemens and Omron PLC systems would be advantageous, but not essential

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Jobs

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Jobs

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Jobs

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.