Data Engineer Apprentice

DiverseJobsMatter
Milton Keynes
1 week ago
Applications closed

Related Jobs

View all jobs

Senior Data and Analytics Manager

Head of Data & AI

Head of Data & AI

Data Engineer

Data Engineer

Data Engineer

Please note that this is an apprenticeship position and therefore anyone who holds a degree or masters degree in a subject such as Data Science will not be eligible.You will also need to commit to completing a Level 5 Data Engineer Apprenticeship.

What will you be doing?

Working in our data team as part of our Customer Experience (CX) function, you’ll be instrumental in building data products that are customer focussed and deliver business value. As part of this you will:

  • Identify and evaluate opportunities to acquire, enrich and deliver enhanced insight from data.
  • Analyse requirements, explore options and present recommendations for solutions to stakeholders.
  • Build and optimise automated data solutions and pipelines.
  • Keep up to date with data engineering developments to advance your own skills and knowledge.

As part of the Level 5 Data Engineer apprenticeship standard, you’ll be on track to an industry recognised qualification and your dedicated industry coach will support you through a blended approach that will include remote, in person, 1-2-1 and group learning.

What do you need?

To be successful in this apprenticeship you'll have high levels of accuracy and attention to detail. You should be competent using Microsoft Excel and have a proven interest in data analysis (this could be from formal studies, self-study or the workplace). You will have a proven aptitude in working with numbers, you may have a level 3 or level 4 in a relevant subject and be looking to take the next step in your data career. Some experience of using data tools (e.g SQL, Python, Power BI etc) would be an advantage but not essential.

To be eligible for the apprenticeship, you also need to have a minimum of 5 GCSEs (grades 9-4 or A-C) including Maths and English.

You also need to meet the government eligibility criteria, including:

Right to Work: You must have the right to work in the UK.

Residency: you must meet one of the following:

  • A UK citizen who has been resident in the UK or EEA for the previous three years.
  • An EEA or Switzerland national who has obtained either pre-settled or settled status under the EUSS and have lived continuously in the EEA, Switzerland, Gibraltar, or the UK for at least the previous 3 years.
  • A non-UK national who has been ordinarily resident in the UK and Islands for at least the previous 3 years where no part of this period has been wholly or mainly for the purpose of receiving full-time education. E.g. time undertaking a degree or Masters degree as an overseas student does not count towards the 3 years.
  • An individual with immigration or asylum-seeking status which makes you eligible to receive government apprenticeship funding.

Prior knowledge and skills: You must not hold a level 5 qualification or above in a related subject, e.g. a degree or masters degree in subjects including Maths, Data Analysis, Business Analytics etc.

Government funded learning programmes: You must not be on another government funded learning programme

What's in it for you?

You’ll be working towards your level 5 Data Engineer apprenticeship over 2 years to gain a recognised qualification alongside industry experts. As well as a salaryof £23,000, you'll also be eligible for a new car every six months (as long as you have a full, clean UK driving licence). You’ll receive 27 days holiday – plus bank holidays, access to our pension scheme, employee well-being support, on-site restaurant and shopping discounts.

What's the assessment process?

Once you hit the apply button, you will be asked to submit an application form with CV and answer a couple of video interview questions so that we have a chance to get to know a little more about you.

Our final step in the journey would be to attend a face-to-face interview, where you will take part in a range of activities based on real life tasks.

Successful candidates will be offered a place soon afterwards for a September 2025 start.`

By applying you are agreeing to share your information with Digital Native, our apprenticeship training provider.

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Tips for Staying Inspired: How Data Science Pros Fuel Creativity and Innovation

Data science sits at the dynamic intersection of statistics, computer science, and domain expertise, driving powerful innovations in industries ranging from healthcare to finance, and from retail to robotics. Yet, the daily reality for many data scientists can be a far cry from starry-eyed talk of AI and machine learning transformations. Instead, it often involves endless data wrangling, model tuning, and scrutiny over metrics. Maintaining a sense of creativity in this environment can be an uphill battle. So, how do successful data scientists continue to dream big and innovate, even when dealing with the nitty-gritty of data pipelines, debugging code, or explaining results to stakeholders? Below, we outline ten practical strategies to help data analysts, machine learning engineers, and research scientists stay inspired and push their ideas further. Whether you’re just starting out or looking to reinvigorate a long-standing career, these pointers can help you find fresh sparks of motivation.

Top 10 Data Science Career Myths Debunked: Key Facts for Aspiring Professionals

Data science has become one of the most sought-after fields in the tech world, promising attractive salaries, cutting-edge projects, and the opportunity to shape decision-making in virtually every industry. From e-commerce recommendation engines to AI-powered medical diagnostics, data scientists are the force behind innovations that drive productivity and improve people’s lives. Yet, despite the demand and glamour often associated with this discipline, data science is also shrouded in misconceptions. Some believe you need a PhD in mathematics or statistics; others assume data science is exclusively about machine learning or coding. At DataScience-Jobs.co.uk, we’ve encountered a wide array of myths that can discourage talented individuals or mislead those exploring a data science career. This article aims to bust the top 10 data science career myths—providing clarity on what data scientists actually do and illuminating the true diversity and inclusiveness of this exciting field. Whether you’re a recent graduate, a professional looking to pivot, or simply curious about data science, read on to discover the reality behind the myths.

Global vs. Local: Comparing the UK Data Science Job Market to International Landscapes

How to evaluate salaries, opportunities, and work culture in data science across the UK, the US, Europe, and Asia Data science has proven to be more than a passing trend; it is now a foundational pillar of modern decision-making in virtually every industry—from healthcare and finance to retail and entertainment. As the volume of data grows exponentially, organisations urgently need professionals who can transform raw information into actionable insights. This high demand has sparked a wave of new opportunities for data scientists worldwide. In this article, we’ll compare the UK data science job market to those in the United States, Europe, and Asia. We’ll explore hiring trends, salary benchmarks, and cultural nuances to help you decide whether to focus your career locally or consider opportunities overseas or in fully remote roles. Whether you’re a fresh graduate looking for your first data science position, an experienced data professional pivoting from analytics, or a software engineer eager to break into machine learning, understanding the global data science landscape can be a game-changer. By the end of this overview, you’ll be better equipped to navigate the expanding world of data science—knowing which skills and certifications matter most, how salaries differ between regions, and what to expect from distinct work cultures. Let’s dive in.