Data Technician Apprentice
KAINUU LTD
Manchester (OL8 1AA)
Closes in 30 days (Thursday 2 April 2026)
Posted on 2 March 2026
Contents
Summary
The role at Elliotts includes all general admin duties, including sending emails, answering calls, serving customers and contacting suppliers, and all aspects of customer service whilst requiring additional flexibility.
- Wage
-
£14,722.50 for your first year, then could increase depending on your age
National Minimum Wage rate for apprentices
- Training course
- Data technician (level 3)
- Hours
-
Monday to Friday, working hours TBC
37 hours 30 minutes a week
- Start date
-
Saturday 2 May 2026
- Duration
-
1 year 4 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 learn how to:
- Serving customers on the front desk
- Managing paperwork
- Scanning and filing away documents
- Sending relevant documents off
- Contacting suppliers
- Managing designated corporate customer accounts to ensure high levels of customer service provided and maintained
- Handling enquiries by email or telephone and assisting customers when required. Building effective relationships with customers and colleagues to ensure a high level of customer service is given
- Effective and efficient use of the ProHire system
- Access to spreadsheets and basic reporting
- Opportunity to move and manage data
- Opportunity to cleanse data from the CRM/system
- Updating ProHire with information and dates
- Develop an understanding of relevant vehicle legislation
Where you'll work
Oldham
Manchester
OL8 1AA
Training
Apprenticeships include time away from working for specialist training. You’ll study to gain professional knowledge and skills.
Training provider
NOWSKILLS 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
Data Technician Level 3.
More training information
Apprenticeships include time away from working for specialist training. You’ll study to gain professional knowledge and skills.
Requirements
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
- Problem solving skills
- Administrative skills
- Initiative
Other requirements
- Strong communication skills and the ability to use these with a wide range of people
- Positive attitude
- Ability to be proactive and look for opportunities to improve the working environment
- Previous customer service experience, strong attention to detail and excellent written and verbal communication skills including call handling
- Able to work confidently under their own initiative and look at problem solving with a solutions-based approach
- Proven ability to build and maintain working relationships with a wide range of customers as well as colleagues
- Able to work effectively as a team as well as independently
- Confident in managing their own workload as well as that of others and able to not only motivate themselves but also others throughout the process
- Good attention to detail; able to work with data quickly and accurately
About this employer
Our Digital Marketing, IT Infrastructure, Content Creation, and Data Analytics apprenticeships are designed in collaboration with employers. We combine expert teaching and learning with real-world experience to equip our apprentices with the skills, knowledge, attitudes and behaviours for a successful career.
After this apprenticeship
The successful candidate may be offered full-time employment.
Ask a question
The contact for this apprenticeship is:
NOWSKILLS LIMITED
The reference code for this apprenticeship is VAC2000018647.
Apply now
Closes in 30 days (Thursday 2 April 2026)
After signing in, you’ll apply for this apprenticeship on the company's website.