Summary
As an ERP & Data Apprentice, you will learn how the system works and assist with keeping data accurate and up to date. You will help maintain product information, support colleagues who use the system, and contribute to improving how data flows through the business.
Wage
£19,218.75 a year
Training course
Data technician (level 3)
Hours
Working hours: Monday to Thursday, 8:00am – 4:30pm, and Friday, 8:00am – 3:00pm.
37 hours 30 minutes a week
Start date
Monday 22 June 2026
Duration
1 year 3 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
* Support the accuracy and maintenance of data within the ERP system
* Assist with testing system updates and improvements under guidance
* Help analyse and organise product and process data.
* Support the setup and configuration of system information as required.
* Provide basic user assistance and help colleagues with simple system queries once trained
* Run and prepare reports from the ERP system to support different department
* Support the creation and updating of documentation, such as instructions and training guides.
* Work with different departments to ensure data is entered correctly and processes run smoothly
Where you'll work
UNIT 2 ANGELS CLOSE
AYCLIFFE INDUSTRIAL PARK
NEWTON AYCLIFFE
COUNTY DURHAM
DL5 6BG
Training
Apprenticeships include time away from working for specialist training. You’ll study to gain professional knowledge and skills.
Training provider
BALTIC TRAINING SERVICES 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
Baltic Apprenticeships were the first training provider to offer a completely tech-focused, tech-driven training solution. We help people transform their knowledge and passion into skills that employers need.
This apprenticeship will teach you essential data skills, including how to source, format and present data; data validation and analysis; and how to apply legal and ethical principles when gathering and manipulating business data.
Requirements
Essential qualifications
GCSE in:
* English (grade 4)
* Math (grade 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
* Attention to detail
* Organisation skills
* Problem solving skills
* Administrative skills
* Analytical skills
* Team working