Data Support Apprentice
COX AUTOMOTIVE UK LIMITED
Stafford (ST16 2HQ)
Closes in 28 days (Tuesday 20 January 2026)
Posted on 23 December 2025
Contents
Summary
This role supports the Sales Enablement team in driving productivity and performance across our sales organisation. The successful candidate will explore the use of AI tools to enhance efficiency, analyse sales and training data to identify trends, and assist in writing clear, structured processes.
- Wage
-
£21,000 a year
- Training course
- Data technician (level 3)
- Hours
-
Shifts to be confirmed between the hours of 9.00am - 5.30pm
38 hours a week
- Start date
-
Tuesday 27 January 2026
- Duration
-
1 year 5 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
- Support AI exploration to identify tools that enhance sales productivity
- Assist with data analysis to track performance and identify trends
- Contribute to process documentation for enablement workflows and best practices
- Help create and update training materials for sales onboarding and development
- Coordinate enablement activities, including workshops and communications
- Maintain internal documentation and shared resources for the team
- Support reporting tasks, including dashboards and performance summaries
- Engage with stakeholders across sales, training, and operations
- Participate in team projects, offering admin and creative input
- Develop core business skills, including time management and communication
Where you'll work
16 & 17 Waterfront Way
Stafford
ST16 2HQ
Training
Apprenticeships include time away from working for specialist training. You’ll study to gain professional knowledge and skills.
Training provider
QA 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
Why choose our Data Essentials Apprenticeship?
QA’s Data Essentials Level 3 apprenticeship can support your business to be more productive with data and adapt to a modern-day workplace. Data available to organisations is increasing at scale. How your business leverages it is essential to successful transformation and continued growth.
QA's Data Essentials Level 3 apprentice will learn to:
- Source, format and present data securely, using Microsoft Excel, Power BI and SQL
- Analyse structured and unstructured data to support business outcomes
- Blend data from multiple sources as directed
- Communicate outcomes appropriate to the audience
- Apply legal and ethical principles when manipulating data
QA’s Data Essential Level 3 apprenticeship programme enables your organisation to:
- Build the capabilities you need throughout your organisation to collect, study, organise and present data, increasing digital adoption and the provision of intelligent and valuable business insights
- Create and develop analysts for the modern workplace by reskilling your existing talent, or hiring new entry-level talent. QA’s programmes, partnerships and recruitment capability enable us to tailor a solution that works for your business
- Provide training that acts as a standalone solution or as part of a wider academy/programme to an array of business functions
Tools and technologies learned: Apprentices will learn to use Microsoft Excel and Power BI.
Requirements
Essential qualifications
GCSE in:
- 3 of any subject (grade 4+ (A* - C))
- Maths & English (grade 3+ (D or above))
Share if you have other relevant qualifications and industry experience. The apprenticeship can be adjusted to reflect what you already know.
Skills
- Communication skills
- IT skills
- Attention to detail
- Organisation skills
- Number skills
- Analytical skills
- Team working
About this employer
Cox Automotive is a global automotive services and technology company that helps dealers, manufacturers, and buyers buy, sell, and manage vehicles through data, digital platforms, and vehicle services.
Company benefits
- Volunteer day
- Birthday day
- Well-being day
- Access to high street discounts
- Pension contributions
- Cycle to work scheme
After this apprenticeship
- 90% of QA apprentices secure permanent employment after completing: this is 20% higher than the national average
Ask a question
The contact for this apprenticeship is:
QA LIMITED
The reference code for this apprenticeship is VAC2000006406.
Apply now
Closes in 28 days (Tuesday 20 January 2026)
After signing in, you’ll apply for this apprenticeship on the company's website.