Data Analyst Apprenticeship
CAME UK Ltd
UK (DE74 2US)
Closes in 27 days (Friday 27 February 2026)
Posted on 30 January 2026
Contents
Summary
Are you looking to build a long-term career working with data? Then look no further! Start your career today with a level 3 data User apprenticeship with CAME UK and Kaplan. You will be gaining valuable workplace experience whilst working towards the qualification.
- Wage
-
£18,000 a year
- Training course
- Data technician (level 3)
- Hours
-
Between 9am - 5pm, Monday to Friday.
35 hours a week
- Start date
-
Monday 2 March 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
During this apprenticeship your roles and responsibilities will include:
- Manage, update, and maintain data primarily using Excel
- Ensure accuracy and consistency through regular data checks and validation
- Organise spreadsheets to support tracking, reporting, and analysis
- Use basic Excel functions (e.g. formulas, filters) to manipulate and analyse data
- Produce simple reports to support day-to-day operations and decision-making
Where you'll work
Unit 1B, Sills Road
Castle Donnington
Derby
UK
DE74 2US
Training
Apprenticeships include time away from working for specialist training. You’ll study to gain professional knowledge and skills.
Training provider
KAPLAN FINANCIAL 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
This apprenticeship provides your employees with fundamental capabilities crucial for navigating and leveraging data effectively within your organisation, allowing them to understand insights, foster transformation, and gain a competitive edge.
- Data Analysis Fundamentals
- Data Literacy and Generative AI Introduction
- Data Analysis and Visualisation with Excel
- Databases and Data Modelling
- Data Challenge and EPA Readiness
Our apprenticeships are uniquely designed to offer unparalleled support for both employers and learners. We provide expert-led, practical training and simulations that build transferable digital skills and instil a growth mindset – essential for effectively leveraging technology.
Requirements
Essential qualifications
GCSE or equivalent 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
- Administrative skills
- Number skills
- Analytical skills
- Logical
- Team working
- Initiative
- Non judgemental
Other requirements
Park available / public transport reasonable.
About this employer
For over 50 years, we at CAME have designed and produced high-quality technological products and solutions for the comfort and security of people in residential, public and business environments. Thanks to the trust of our customers, we have become a go-to brand and global partner for automation, smart homes, access control and security and parking systems.
After this apprenticeship
Potential growth within data roles (Data Analyst).
Ask a question
The contact for this apprenticeship is:
KAPLAN FINANCIAL LIMITED
The reference code for this apprenticeship is VAC2000012002.
Apply now
Closes in 27 days (Friday 27 February 2026)
After signing in, you’ll apply for this apprenticeship on the company's website.