RLT GROUP GLOBAL LTD
Wage: £22,425 a year
Training course: Data technician (level 3)
Hours: Monday to Friday, working hours TBC
Start date: Monday 18 May 2026
Duration: 1 year 4 months
Positions available: 1
Do you thrive in a fast-paced environment where exceptional customer service meets technical expertise and innovative technology? At RLT Group Global Ltd, our mission is to simplify life for our clients in the electrical and facilities maintenance industry. We foster a culture built on energy, integrity, innovation, and teamwork.
Wage £22,425 a year Check minimum wage rates (opens in new tab) Training course Data technician (level 3) Hours Monday to Friday, working hours TBC 45 hours a week Start date Monday 18 May 2026 Duration 1 year 4 months Positions available 1
Champion Customer Success: Deliver exceptional customer service on calls, emails, and in-person interactions, upholding RLT Group’s core values of energy, integrity, innovation, and teamwork Order Processing & Quotation Management: Handle incoming orders, create accurate quotations, and manage follow-ups with clients and suppliers efficiently Data Entry & Analysis: Maintain accurate client and order data, analyse trends, and generate insights to support strategic decision-making AI Tool Automation: Implement and leverage AI tools to automate routine tasks, improve response times, and enhance workflow efficiency Procedure Automation: Identify opportunities to automate processes across order processing, returns management, and quotation generation Technical Liaison: Collaborate with suppliers to ensure timely delivery of electrical and facilities maintenance spares, keeping customers informed of expected arrivals Customer Process Optimisation: Streamline order processing, quotation creation, returns, and collections to improve speed, accuracy, and customer satisfaction Support Sales & Reporting: Identify opportunities to generate additional revenue for existing clients using data insights, technical knowledge, and process improvements Foster a Collaborative Spirit: Promote teamwork and a positive environment where innovation, problem-solving, and a “can-do” attitude thrive
UNIT 3ALBRIGHT ROADWIDNESCHESHIREWA8 8FY
Apprenticeships include time away from working for specialist training. You’ll study to gain professional knowledge and skills.
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.
Data Technician Level 3.
Share if you have other relevant qualifications and industry experience. The apprenticeship can be adjusted to reflect what you already know.
Communication skillsAttention to detailOrganisation skillsProblem solving skillsAdministrative skillsTeam workingInitiativeFull UK driving license
We could call this page, “about us”, but really, “about you” would be better. Put simply, we are simply all about making life easier for you.
This isn’t just because it’s a good thing to do (although it is). It’s because years of experience in the supply of lighting and other consumables to the FM sector has shown us that through making life easier for you based on LEAN thinking, we can have a serious impact on reducing your costs. We’re not scared of thinking a little boldly to transform the way the market works, so long as it fits with our mission.
https://www.rltgroup.co.uk/ (opens in new tab)
The successful candidate may be chosen to have a full-time role after completing their apprenticeship.
Interested in this role?