Highways Systems and Data Apprentice

Summary

Warwickshire County Council is looking for an enthusiastic and motivated Apprentice Highways Systems and Data Officer to join our Highway Systems Team. This is an exciting opportunity to develop a career in digital systems, data analysis and technology.

Wage

£20,947.09 a year

Pay will increase in line with NMW rates based on age.

Training course

Data technician (level 3)

Hours

Monday to Friday, generally 9.00am - 5.00pm, but in line with our flexible working policy.

37 hours a week

Start date

Monday 12 October 2026

Duration

2 years

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 Highways Systems and Data Officer, you'll gain key knowledge and skills by supporting the following daily tasks:

• Supporting the administration and maintenance of highways systems and applications
• Helping investigate and resolve routine system issues
• Producing reports and performance information using highways data
• Assisting with data quality improvement initiatives and data validation activities
• Analysing information to identify trends and opportunities for service improvement
• Supporting system testing, upgrades and new functionality implementations
• Helping document business processes, user guidance and system procedures
• Assisting with digital transformation projects and system integrations
• Working collaboratively with colleagues, suppliers and stakeholders across the service
• Providing support and guidance to system users
• Developing practical skills in data analysis, business processes, digital technologies and continuous improvement

Where you'll work

160 Old Budbrooke Road
Budbrooke
Warwick
CV35 7DY

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)

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 apprenticeship will provide you with the Level 3 Technician apprenticeship qualification, delivered by our training provider QA.

The 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 for personalised coaching and support. These specialists ensure your successful progress, support your well being, and enable your readiness for assessments.

Requirements

Desirable qualifications

GCSE in:

• English (grade 9 - 4)
• Maths (grade 9 - 4)

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
• Administrative skills
• Number skills
• Team working
• Initiative
• Non judgemental
• Patience