Summary Brash Solutions is currently recruiting for a bright, friendly and enthusiastic AI & Digital Support Apprentice to work in our offices in Berkhamsted. Working within a small team of experienced Support Technicians, you will be taking calls from our client’s staff and assist them with a wide variety of IT queries. Wage £18,000 a year Check minimum wage rates (opens in new tab) Training course Data technician (level 3) Hours 8:30am to 5:30pm, Monday to Friday 40 hours a week Start date Monday 25 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 Be a friendly face of IT while users are experiencing problems Taking requests from users via email, ticketing system and telephone Adhere to challenging SLA requirements, logging full details of time and work undertaken Completing initial troubleshooting in a timely manner Monitor the support ticket system for incidents requiring escalation or urgent attention Build and maintain desktop/laptop PCs/Macs and Windows Servers Follow and apply IT policies and procedures applicable to each client Help and advise on digital and AI requirements from clients Diagnose and resolve hardware and software faults System health checks Software and app support Where you'll work SUITE S 18-20 18-20 AUDLEY HOUSE NORTH BRIDGE ROAD BERKHAMSTED HP4 1EH 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 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 Customer care skills Problem solving skills Team working About this employer Established in 2001, Brash Solutions provides complete business solutions to a variety of industrial and commercial organisations. We have a highly professional and experienced team of support engineers and software developers. Our support business aims to meet all the IT requirements of our clients, from setting up new starters, troubleshooting issues to keeping their networks secure. We pride ourselves on the personal touch, understanding each client’s needs and building strong relationships. Company benefits 20 days holiday (pro rata) bank holidays State pension Free parking 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 VAC2000027422.