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- Tasks: Collect, clean, and visualise data in a dynamic automotive environment.
- Company: Leading automotive company in Milton Keynes with a focus on innovation.
- Benefits: Earn £20,000, enjoy 27 days' holiday, and access additional perks.
- Why this job: Gain valuable industry experience while working towards a recognised qualification.
- Qualifications: Must have high accuracy, attention to detail, and familiarity with Excel.
- Other info: Perfect for those with at least 5 GCSEs looking to kickstart their career.
The predicted salary is between 1200 - 1400 £ per month.
A leading automotive company in Milton Keynes is looking for candidates for a Level 3 Data Technician apprenticeship. This position involves collecting, cleaning, and visualizing data, and offers a salary of £20,000 alongside 27 days' holiday and additional benefits.
Candidates must have high accuracy, attention to detail, and familiarity with Excel, as well as meet eligibility criteria including a minimum of 5 GCSEs.
This apprenticeship provides the opportunity to gain valuable industry experience and a recognized qualification.
Data Technician Apprentice — Level 3 (Blended Learning) in Milton Keynes employer: Volkswagen Group UK
Contact Detail:
Volkswagen Group UK Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Technician Apprentice — Level 3 (Blended Learning) in Milton Keynes
✨Tip Number 1
Network like a pro! Reach out to current or former employees of the company on LinkedIn. A friendly chat can give us insider info and maybe even a referral!
✨Tip Number 2
Prepare for the interview by practising common questions related to data handling and Excel. We can even role-play with a friend to boost our confidence!
✨Tip Number 3
Showcase your skills! Bring along examples of any data projects you've worked on, even if they're just personal projects. This will help us stand out from the crowd.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed and we can track our progress easily.
We think you need these skills to ace Data Technician Apprentice — Level 3 (Blended Learning) in Milton Keynes
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with data, especially if you've worked with Excel. We want to see how you can collect, clean, and visualise data, so don’t hold back on showcasing your skills!
Attention to Detail is Key: Since this role requires high accuracy, it’s crucial to demonstrate your attention to detail in your application. Use examples from your past experiences where you’ve had to be meticulous and precise.
Tailor Your Application: Don’t just send a generic application! We love seeing candidates who take the time to tailor their CV and cover letter to the specific role. Mention why you’re excited about the Data Technician apprenticeship and how it aligns with your career goals.
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to follow the process step-by-step without any hassle!
How to prepare for a job interview at Volkswagen Group UK
✨Know Your Data
Make sure you brush up on your data skills before the interview. Familiarise yourself with data collection, cleaning, and visualisation techniques. Being able to discuss these topics confidently will show that you're serious about the role.
✨Excel is Key
Since familiarity with Excel is a must, practice using it to manipulate data sets. Be prepared to talk about any projects you've done using Excel, and if possible, bring examples of your work to showcase your skills.
✨Attention to Detail Matters
Highlight your attention to detail during the interview. You might be asked to solve a problem or analyse a dataset, so demonstrate how you approach tasks methodically and ensure accuracy in your work.
✨Ask Insightful Questions
Prepare some thoughtful questions about the apprenticeship and the company. This shows your interest and enthusiasm for the role. Ask about the types of projects you might work on or how the team collaborates on data tasks.
