Summary
We are looking for an enthusiastic and motivated First-Line IT Support Technician Apprentice to join our team as part of the Digital & AI Support Level 3 apprenticeship. This is a fantastic opportunity for someone looking to start their career in IT and digital support while developing modern, in-demand skills.
Wage
£17,000 a year
Training course
Data technician (level 3)
Hours
Monday - Friday, Shifts to be confirmed.
40 hours a week
Start date
Monday 6 July 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
First-Line Support: Act as the initial point of contact for clients reporting technical issues via phone, email, or ticketing systems.
Troubleshooting & Resolution: Diagnose and resolve common technical issues relating to:
* Hardware (PCs, laptops, printers)
* Operating systems (Windows, macOS)
* Software applications (including Microsoft 365 / Office)
User Management: Assist with basic user administration tasks, such as:
* Setting up new user accounts
* Password resets
* Managing security group access within Active Directory and Microsoft 365
* Documentation: Accurately log support requests, actions, and resolutions within the ticketing system and contribute to internal knowledge base articles
* Hardware Setup: Assist with the preparation, installation, and deployment of new hardware and software for clients
* Customer Service: Provide a professional, friendly, and patient approach at all times, ensuring a high level of customer satisfaction
Where you'll work
Holmer Road
Hereford
HR4 9SZ
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)
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 AI & Digital Support?
This programme brings together AI, Microsoft Copilot and broader digital skills to provide support and advice to users across a wide range of business software and Generative AI applications, enhancing digital transformation and increasing AI literacy across your organisation.
* Accelerate AI adoption
* Streamline productivity
* Champion innovation
The AI & Digital Support programme integrates live and online workshops with self-paced learning, employing a guided discovery approach for individual learner contexts.
Learners are assigned a Digital Learning Consultant (DLC) for personalised coaching and support. These specialists ensure their successful progress, wellbeing, and readiness for assessments.
Apprentices will learn to use a variety of tools and technologies, including:
* Microsoft 365
* Microsoft Copilot
* SaaS (Software as a Service) applications
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
* UK driving licence