Data Technician Apprenticeship

NET PLATES LTD

Solihull (B90 4QT)

Closes in 26 days (Tuesday 31 March 2026)

Posted on 4 March 2026

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Summary

Netplates is looking for a detail-oriented and analytical Data Technician Apprentice to join their team. This is an exciting opportunity to develop strong data, reporting, and analytical skills while gaining valuable exposure to company accounts and financial processes.

Wage

£22,350 a year

Check minimum wage rates (opens in new tab)

Training course
Data technician (level 3)
Hours
Monday to Friday 9am to 5pm.

37 hours 30 minutes a week

Start date

Wednesday 1 April 2026

Duration

1 year 3 months

Positions available

1

Work

Most of your apprenticeship is spent working. You’ll learn on the job by getting hands-on experience.

What you'll do at work

  • You will support the business by collecting, organising, and analysing data to help improve performance, efficiency, and decision-making across departments
  • Collecting, inputting, and maintaining accurate company data
  • Assisting with data analysis and generating reports for management
  • Supporting the preparation of performance dashboards and KPI reports
  • Ensuring data quality, consistency, and compliance
  • Assisting with basic financial data entry and reconciliation tasks
  • Supporting accounts processes, including invoice tracking and payment records
  • Identifying trends or discrepancies within datasets
  • Maintaining confidentiality of financial and company information

Where you'll work

Unit E, Swallows Industrial Estate
267 Cranmore Boulevard
Shirley
Solihull
B90 4QT

Training

Apprenticeships include time away from working for specialist training. You’ll study to gain professional knowledge and skills.

Training provider

METAGEDU APPRENTICESHIPS LTD

Training course

Data technician (level 3)

Understanding apprenticeship levels (opens in new tab)

What you'll learn

Course contents
  • Select and migrate data from already identified sources.
  • Format and save datasets.
  • Summarise, analyse and explain gathered data.
  • Combine data sets from multiple sources and present in format appropriate to the task.
  • Use tools and/or apply basic statistical methods to identify trends and patterns in data.
  • Identify faults and cleanse data to improve data quality, for example identifying gaps, duplicate entries, outliers and unusual variances, including cross-checking across data elements or between data sources.
  • Audit data results for maintenance of data quality, reviewing a data set once all sources are combined, to ensure accuracy, completeness, consistency and traceability from original data.
  • Demonstrate the different ways of communicating meaning from data in line with audience requirements.
  • Produce clear and consistent documentation of the data provided to others and of actions completed. Where appropriate or mandated by the working context, this documentation should use standard organisational templates.
  • Store, manage and distribute data in compliance with organisational, national, sector specific standards and or legislation.
  • Considers sustainability and ways to reduce impact. For example, using cloud storage, sharing links to files, avoid storing multiple versions of files, and reducing the use of physical handouts of documentation.
  • Parse data against standard formats, and test and assess confidence in the data and its integrity.
  • Operate collaboratively in a working context that accounts for, and takes advantage of, the roles, skills and activities of others, especially those interacting with the same data sets or working towards a common goal.
  • Prioritise own activities within the context of the duties to be performed, taking account of any known or expected impact on others.
  • Follows equity, diversity and inclusion policies in the organisation for a common goal.
  • Demonstrate the ability to use different tools and methods to formulate and utilise effective prompts to research, apply, and evaluate data transformation techniques.
  • Select and migrate data from already identified sources.
  • Format and save datasets.
  • Summarise, analyse and explain gathered data.
  • Combine data sets from multiple sources and present in format appropriate to the task.
  • Use tools and/or apply basic statistical methods to identify trends and patterns in data.
  • Identify faults and cleanse data to improve data quality, for example identifying gaps, duplicate entries, outliers and unusual variances, including cross-checking across data elements or between data sources.
  • Audit data results for maintenance of data quality, reviewing a data set once all sources are combined, to ensure accuracy, completeness, consistency and traceability from original data.
  • Demonstrate the different ways of communicating meaning from data in line with audience requirements.
  • Produce clear and consistent documentation of the data provided to others and of actions completed. Where appropriate or mandated by the working context, this documentation should use standard organisational templates.
  • Store, manage and distribute data in compliance with organisational, national, sector specific standards and or legislation.
  • Considers sustainability and ways to reduce impact. For example, using cloud storage, sharing links to files, avoid storing multiple versions of files, and reducing the use of physical handouts of documentation.
  • Parse data against standard formats, and test and assess confidence in the data and its integrity.
  • Operate collaboratively in a working context that accounts for, and takes advantage of, the roles, skills and activities of others, especially those interacting with the same data sets or working towards a common goal.
  • Prioritise own activities within the context of the duties to be performed, taking account of any known or expected impact on others.
  • Follows equity, diversity and inclusion policies in the organisation for a common goal.
  • Demonstrate the ability to use different tools and methods to formulate and utilise effective prompts to research, apply, and evaluate data transformation techniques.

Training schedule

This training schedule has not been finalised. Check with this employer if you’ll need to travel to a college or training location for this apprenticeship.

Requirements

Essential qualifications

GCSE in:

  • English (grade 4)
  • Maths (grade 4)

Share if you have other relevant qualifications and industry experience. The apprenticeship can be adjusted to reflect what you already know.

Skills

  • IT skills
  • Attention to detail
  • Organisation skills
  • Problem solving skills
  • Number skills
  • Analytical skills
  • Logical

Other requirements

  • Strong Excel skills (formulas, Pivot Tables)
  • Understanding of data structures and databases
  • Basic knowledge of SQL or Power BI (desirable but not essential)
  • Strong analytical thinking

About this employer

Netplates.co.uk stands as an e-commerce enterprise specialising in the purchase and sale of personalised cherished registrations within the United Kingdom. Their focus lies in delivering vehicle registration numbers tailored to your specific needs. As a growing employer, Netplates values continuous improvement, invests in its people, and strives to create a positive, supportive workplace environment where employees can develop their skills and contribute to long-term business success.

 

https://netplates.co.uk/ (opens in new tab)

Company benefits

Pension. Employer discounts

After this apprenticeship

Progressional opportunities to work towards Data Analyst L4 Apprenticeship. 

Ask a question

The contact for this apprenticeship is:

METAGEDU APPRENTICESHIPS LTD

The reference code for this apprenticeship is VAC2000019103.

Apply now

Closes in 26 days (Tuesday 31 March 2026)

After signing in, you’ll apply for this apprenticeship on the company's website.