Automation Systems Engineer

Westport
9 months ago
Applications closed

Related Jobs

View all jobs

Azure Data Engineer - Outside IR35 - Hybrid 3 Days in London

Data Engineer

Senior Data Engineer

Data Warehouse Engineer

Data Engineer

Senior Data Engineer

Automation Systems Engineer
Westport, Ireland
Who We are:
NIRAS employs over 3000 permanent staff and a pool of over 25,000 experts and consultants working across our international network of 51 offices in 32 countries around the world.
Position Opportunity:
NIRAS Ireland are currently recruiting, a dynamic and enthusiastic Operational Technology Systems Engineer to be based on site at our clients advanced technology manufacturing facility, based in the beautiful West of Ireland. The successful candidate will support lifecycle management of Operational Technology Systems & applications across the Westport Manufacturing Site. The OT Systems Engineer will be expected to support all aspects of the Production OT systems and provide development and installation support for new hardware and software solutions. This is a 12 month contract.
Responsibilities

  • Support of Operating System platforms and OT software applications
  • Provision of technical support and direction to Manufacturing Operations, Validation Engineers, and IT support staff as part of Manufacturing project support and project execution including transfer to production.
  • Provision of support for root cause problem solving and the implementation of CAPA’s.
  • Follow the clients OT lifecycle management processes to meet or exceed regulatory expectation in respect of data integrity: data backup regimes and system recovery testing.
  • Assist with design and build of secure, robust, highly available fit‐for‐purpose and future proofed application environments.
  • Creation of technical documents required to complete SDLC document set, and knowledge articles required by Tier 2 and Tier 3 support teams.
  • Support any safety or quality initiatives that require Operational Technology support.
  • Support cost savings initiatives onsite and within the Automation team
  • Participate in departmental and customer project status update meetings.
  • Support operational excellence activities to continuously improve our processes and eliminate waste.
    Qualifications and Experience Requirements:
  • Bachelor’s degree in information technology, Computer Engineering, or related discipline / equivalent experience.
  • Extensive experience delivering automation projects - PLC and SCADA.
  • 3 - 5 years’ experience delivering IT services preferably within Pharmaceutical and/or medical device industries.
  • System Admin Windows 10 and Windows Server 2012/2016/2019
  • Aseptic Processing and or Packaging Equipment experience.
  • Expertise in SCADA, Historian, Thin Client Manager, Active Directory and group policy permissions, XML/XSL, SQL DBA and the development of SQL Queries, Stored Procedures and Reporting.
  • Experience with delivering complex projects, ideally related to manufacturing modernization / manufacturing system upgrades to support business critical process equipment.
  • Good analytical skills and a proven ability to problem solve and identify CAPAs for deviations relating to bugs, failures, and non‐conformances.
  • Strong verbal and written communication skills.
    What to Do next
    If you are looking for an opportunity to advance in your career as an Operational Technology Systems Engineer where you can make an impact on the world, come join our team at NIRAS Ireland where we will encourage you to develop your professional career, flourish and achieve your fullest professional potential.
    For a confidential discussion regarding this and our many other exciting opportunities with NIRAS Ireland, please contact Philip Cahill at (phone number removed) or (phone number removed)

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.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.