Apprentice Product Data Assistant

Beedspeed

GRIMSBY (DN31 2QL)

Closes in 19 days (Sunday 1 February 2026 at 11:59pm)

Posted on 13 January 2026

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Summary

We are looking for a motivated and detail-oriented Apprentice Product Data Assistant to support our growing e-commerce business. This is an excellent opportunity for someone looking to start a career in e-commerce, digital retail, or data management while gaining hands-on experience alongside formal apprenticeship training.

Wage

£14,918.80 for your first year, then could increase depending on your age

National Minimum Wage rate for apprentices

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Training course
Data technician (level 3)
Hours
Monday to Friday 0900-1700

38 hours a week

Start date

Friday 6 February 2026

Duration

2 years

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

  • Listing new products using supplier data feeds and internal product information
  • Updating and maintaining product data, including titles, descriptions, specifications, and pricing
  • Editing and improving product images (cropping, resizing, basic optimisation)
  • Linking products to internal databases and systems to ensure     accurate stock and pricing data
  • Uploading and managing products across multiple marketplaces, including Shopify and eBay
  • Reviewing existing listings and making data improvements where
  • required
  • Assisting with bulk uploads and product data clean-up projects
  • Following internal processes to ensure data accuracy and consistency

 

Where you'll work

1 PYEWIPE ROAD
GRIMSBY
DN31 2QL

Training

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

Training provider

AVANT PARTNERSHIP LIMITED

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

You will be working in Grimsby and one day a fortnight you will attend our training centre to carry out your off the job training.

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
  • Organisation skills
  • Administrative skills
  • Analytical skills
  • Logical
  • Team working
  • Creative
  • Initiative

About this employer

Beedspeed dates back to the early 1980’s, when the company ran scooter parts stalls at scooter rallies around the UK. The first Beedspeed shop was launched in Grimsby in 1983 on Sixhills Street and quickly became a popular parts store and repair shop, where local scooterists and clubs met up to socialize.The shop became more and more popular and grew by word of mouth, advertising in magazines, and by continuing stalls at the National Scooter Rallies.
Beedspeed became the place for parts for you Lambretta and Vespa in the UK.
 In the early 2000’s, Beedspeed moved to its current location on Corporation Road, Grimsby.
 
 
Here the business continued to flourish, and with the introduction of the website and more advertising started to grow internationally, with the company shipping to all corners of the globe on a weekly basis.
 
  
 
 

http://www.beedspeed.com (opens in new tab)

Disability Confident

Disability Confident

A fair proportion of interviews for this apprenticeship will be offered to applicants with a disability or long-term health condition. This includes non-visible disabilities and conditions.

You can choose to be considered for an interview under the Disability Confident scheme. You’ll need to meet the essential requirements to be considered for an interview.

After this apprenticeship

Once the qualification is completed this will enable you to continue to develop and grow with the company. As a small company that is growing this is an ideal opportunity to get in at the start.

Ask a question

The contact for this apprenticeship is:

AVANT PARTNERSHIP LIMITED

The reference code for this apprenticeship is VAC2000008356.

Apply now

Closes in 19 days (Sunday 1 February 2026 at 11:59pm)