IT Data Technician Apprentice

Summary

Relish School Food are delighted to offer the exciting opportunity to recruit a Data Technician Apprentice to join their expanding business.

Wage

£17,000 a year

Training course

Data technician (level 3)

Hours

Monday- Friday (8:00am- 4:30pm)

37 hours 30 minutes a week

Start date

Monday 28 September 2026

Duration

1 year 6 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

As an apprentice, you’ll work at a company and get hands-on experience. You’ll gain new skills and work alongside experienced staff.

What you’ll do at work

Relish School Food are delighted to offer the exciting opportunity to recruit a Data Technician Apprentice to join their expanding business.

With a passion for freshly cooked food and fantastic customer service, Relish School Food prides itself on its bespoke approach to providing all the required IT systems to support a busy school kitchen.

This role involves working with a range of internal and external stakeholders to support the everyday maintenance and operation of the Relish systems.

Roles and Responsibilities:

• 1st Line support handling
• Security monitoring
• Daily monitoring of data-storage
• Daily cleansing of all stored data
• Daily/weekly/monthly incremental archiving of data
• Reporting and data analysis
• Monitoring usage and reporting of system activity and load balances
• Run functionality testing with the assistance of the development team
• Ensure Relish application documentation is kept up-to-date and amended to include new/updated functionality by the production of both written and audio-visual user guides

Where you'll work

MONARCH HOUSE
CHRYSALIS WAY
EASTWOOD
NOTTINGHAM
NG16 3RY

Training

Apprenticeships include time away from working for specialist training. You’ll study to gain professional knowledge and skills.

Training provider

JUST IT TRAINING 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

Data Technician Level 3 Apprenticeship Standard.
You will also receive full training and support from the Leep Talent Apprenticeship Team to increase your skills.

Requirements

Essential qualifications

GCSE in:

• English (grade 4/C +)
• Maths (grade 4/C +)

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
• Problem solving skills
• Analytical skills
• Logical
• Team working
• Interest/experience App dev
• Interest/experience Web Coding
• Proficient in MS Office
• Can do attitude
• Motivated
• Tech Savvy