Data Technician Apprentice

Summary

We have an exciting opportunity for a motivated Data Technician Apprentice to join our growing administration team at our head office.

As part of this role, you will complete the Level 3 Data Technician Apprenticeship, designed to build your skills in communication, organisation, IT, and business operations.

Wage

£14,560 for your first year, then could increase depending on your age

National Minimum Wage rate for apprentices

Pay increases in line with age and apprenticeship year, in accordance with government guidelines

Training course

Data technician (level 3)

Hours

Monday - Friday, 09:00 - 17:00.

35 hours a week

Start date

Tuesday 1 September 2026

Duration

1 year 8 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

Role Summary:

The Data Technician Apprentice supports Ginger Nut Training by collecting, validating, preparing, and presenting operational data to support quality assurance, compliance, learner progress, and employer reporting. Working within the Delivery Support Team, the role helps ensure data is accurate, timely and useful for decision‑making, while completing the Level 3 Data Technician apprenticeship.

This role may particularly suit someone who enjoys spotting patterns, solving problems, organising information and working with data.

Most work will be managed through clearly defined tasks, project plans and reporting schedules, with support available when priorities change.

Key Responsibilities - without limitation, this role may include the following duties:

Data Collection & Validation:

• Support the collection and validation of learner, employer and operational data
• Assist with checking and improving data accuracy across systems (e.g. learner records, reviews, OTJ evidence)
• Identify missing, inconsistent or incorrect data and flag issues to the appropriate team

Reporting & Dashboards:

• Support the creation of regular learner and employer data reports (e.g. progress reports, engagement summaries)
• Maintain and update dashboards and trackers used by Admin, Quality and Engagement teams
• Assist with preparing data for management reports, SAR/QIP evidence and audit activity
• Preparing reports for clients
• Analysing data to identify patterns as well as using spreadsheets/Power BI for data visualisation to present data.

Funding, Quality & Compliance Support:

• Support the Funding & ILR team with data checks linked to ILR submissions and PDSAT reviews (under supervision)
• Assist with preparing evidence and datasets for quality reviews, audits and inspections
• Help maintain clear data records to support audit readiness and compliance assurance

Systems & Digital Tools:

• Use internal systems and digital tools (e.g. MIS, spreadsheets, CRM system and Learning ePortfolio platform)
• Support data organisation, version control and secure storage in line with data protection requirements
• Learn to produce data visualisations, charts and summaries to support decision‑making

Cross‑Team Support:

• Work collaboratively with Administration, Quality, Funding and Client Engagement Teams
• Respond professionally to internal data requests within agreed timescales
• Participate in team meetings and contribute to continuous improvement discussions
• Support the maintenance and accuracy of contact and engagement data used for B2B employer newsletters and learner communications, ensuring mailing lists are up to date, segmented correctly and compliant with data protection requirements
• Support back-office coordination activities, including learner administration, pipeline tracking, and webinar or meeting scheduling

Where you'll work

37 Queen Street
Colchester
Essex
CO1 2PQ

Training

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

Training provider

GINGER NUT MEDIA 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

This training schedule has not been finalised. Check with this employer if you’ll need to travel to a college or training location for this apprenticeship.

More training information

We'll Teach You:

• Compliance systems
• Apprenticeship administration
• Data management
• Quality assurance processes
• Internal software systems

You will receive:

• A structured induction programme
• Written guidance and process documents
• A dedicated line manager
• Weekly support meetings
• Regular feedback and coaching

Requirements

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
• Problem solving skills
• Logical
• Team working
• Creative
• Initiative
• Flexible and adaptable

Other requirements

• This post is subject to the satisfactory completion of a DBS check