Data Technician Apprentice
KAINUU LTD
Liverpool (L1 8JQ)
Closes in 30 days (Sunday 30 August 2026)
Posted on 30 July 2026
Contents
Summary
As a Data Technician Apprentice, you will support the collection, organisation, analysis and reporting of data to help the business make informed decisions. You will work alongside experienced colleagues who will provide training and support throughout your apprenticeship.
- Wage
-
£15,600 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, Full-time position. Shifts TBC.
37 hours 30 minutes a week
- Start date
-
Wednesday 30 September 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
- Collecting, validating and maintaining accurate data.
- Updating and managing databases and spreadsheets.
- Producing reports, dashboards and data summaries.
- Identifying trends and patterns within data.
- Assisting with data quality checks and ensuring information is accurate.
- Supporting different departments with data requests.
- Learning how to use industry-standard software and reporting tools.
- Maintaining confidentiality and handling data in line with GDPR requirements.
- Working as part of a team while managing your own workload.
Where you'll work
Liverpool
Liverpool
L1 8JQ
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
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
- Organisation skills
- Customer care skills
- Team working
Other requirements
- Has good attention to detail.
- Enjoys working with numbers and data.
- Has strong IT skills and is confident using Microsoft Office, particularly Excel.
- Is organised and able to prioritise tasks.
- Has good communication skills, both written and verbal.
- Is willing to learn and develop new skills.
- Can work independently as well as part of a team.
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.
https://nowskills.co.uk/ (opens in new tab)
Company benefits
- Full training and support throughout your apprenticeship.
- Dedicated workplace mentor.
- Opportunity to gain a nationally recognised Level 3 qualification.
After this apprenticeship
Your earnings can increase over time with an apprenticeship. Find out about potential future pay (opens in new tab).
Successful completion of the apprenticeship may lead to a permanent full-time role, subject to performance and business needs.
Ask a question
The contact for this apprenticeship is:
NOWSKILLS LIMITED
The reference code for this apprenticeship is VAC2000045528.
Apply now
Closes in 30 days (Sunday 30 August 2026)
After signing in, you’ll apply for this apprenticeship on the company's website.