Summary You will have the responsibility of executing the sales enablement and “build-with” strategy for native Microsoft and 3rd party security vendor services. The role is to be a Microsoft Azure, Cloud and AI platforms specialist throughout the UK&I business. Wage £23,810 a year Check minimum wage rates (opens in new tab) Training course Data technician (level 3) Hours Days and shifts to be confirmed. 37 hours 30 minutes a week Start date Friday 7 November 2025 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 Overall workload revenue and profit contribution for Azure, responsible for accurate pipeline and sales forecasting Support the creation of repeatable GTM campaigns that are rolled out through the Infinigate Partner Management teams which drive customer frequency & yield Recruit and manage key strategic Azure resellers growing their revenue and profit to agreed targets Provide insight and recommendations which support the development of Infinigate’s Professional and Managed Service offerings Participate in partner education, events and communication programs, encouraging the utilisation of Infinigate’s GROW and EDGE Work with the Microsoft SMC & GPS Channel Sales teams to ensure effective delivery of programs such as the SureStep program Engage with select security vendors to drive repeatable GTM solutions, offers and campaigns in partnership with the Marketing & Product teams Maintain a constant focus on Partner Satisfaction and achievement of Infinigate’s world-class NPS rating Where you'll work 4-5 Genesis Business Park, Albert Drive Woking GU21 5RW 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 Organisation skills Team working About this employer The Infinigate UK Cloud Sales team is responsible for driving the recruitment, activation and ongoing management of Infinigate Partners (our reseller channel) along with supporting their growth through sales and technical enablement, delivering the associated revenue and profit growth, partner satisfaction and team targets. The team is responsible for owning the overall business relationship with our partners and is the main “face” of the business. Company benefits An exciting range of benefits are available. Click to apply to see the full list of benefits on QA's website. After this apprenticeship Potential full time position upon completion Ask a question The contact for this apprenticeship is: QA LIMITED The reference code for this apprenticeship is VAC1000344971.