Data Engineer - LabVIEW - Aerospace - Oxfordshire

Bond Williams Limited
London
2 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

A rapidly growing specialist manufacturing business is looking to recruit a talented LabVIEW Data Engineer to join their newly established product development program, based in Oxfordshire . This is an exceptional opportunity to be at the forefront of aerospace innovation and take a lead role in the LabVIEW data acquisition system for aero-thermal testing on a new range of jet engines.
The role involves working with a team of highly skilled Engineers, supporting a fast paced development / prototyping environment, automating and streamlining test data acquisition and post-processing workflows in order to rapidly optimising het engine performance through each new iteration.
The LabVIEW Data Engineer will take control of a LabVIEW based, aero-thermal experimental data acquisition system including NI DAQ hardware configuration, LabVIEW software development and supporting data analysis using Python.
Key requirements for LabVIEW Data Engineer:
Proficient in LabVIEW data acquisition software system design and implementation for high temperature and speed systems
A relevant PhD or equivalent industry experience in experimental data capture, data logging in system performance evaluation
Experience in collaborative coding and programming (e.g. C, Python, git)
Along with highly interesting and technical work, a clear career progression path and a fantastic culture, there is a highly competitive salary on offer and excellent benefits including an industry leading pension contribution, private health cover from day one and an impressive company share plan.
If you're passionate about applying your LabVIEW data engineering expertise to solve complex challenges in aerospace technology, we want to hear from you.
Bond Williams Professional Recruitment are an equal opportunity employer and operate as an Employment Business and Recruitment Agency

TPBN1_UKTJ

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.

Careers

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.

Jobs

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.

Education

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.

🍪 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.