The Royal Navy - Mine Warfare Specialist Data Technician Apprenticeship

Royal Navy

Hampshire (PO2 8BY)

Closes on Monday 1 June 2026

Posted on 4 June 2024


Summary

We need to make the seas safe. For our warships, for civilian ships, for everyone. And that’s where you come in. You’ll be at the heart of these missions whether they’re in a Mediterranean port, or on operations in the Persian Gulf. As a Mine Warfare Specialist you’ll lead the way for our fleet, clearing any mines in its path.

Wage

£20,400 a year

Check minimum wage rates (opens in new tab)

• An excellent pension scheme • Subsidised travel and accommodation • Six weeks of paid holiday every year • Free medical and dental care

Training course
Data technician (level 3)
Hours
Shifts to be confirmed, total hours per week: 40.00

40 hours a week

Start date

Tuesday 2 June 2026

Duration

1 year 6 months

Positions available

28

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

You’ll make sure our missions are possible whatever they’re for, from delivering essential humanitarian aid, to embarking on conflict operations.

  • Find mines using sonar, and then launch remote controlled mine disposal vehicles.
  • Gain a wide range of skills, from basic seamanship to manning light weaponry.
  • Be responsible for the safety of your ship and everyone on board.
  • Stay quick thinking and focused at all times. 

Where you'll work

Navy Command HQ
The Admiral Sir Henry Leach Building
Portsmouth
Hampshire
PO2 8BY

Training

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

Training provider

ROYAL NAVY

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

  • By the end of your training you will be a qualified Mine Warfare Specialist (Data Technician) Level 3.
  • Functional Skills in maths and English, if required.

Requirements

Desirable qualifications

GCSE or equivalent in:

Math and English (grade GCSE Level 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
  • Problem solving skills
  • Administrative skills
  • Analytical skills
  • Logical
  • Team working
  • Creative
  • Initiative
  • Non judgemental
  • Patience

Other requirements

No qualifications required – just that you pass a Recruit Test and are in a good state of health and fitness.

About this employer

The Royal Navy (RN) is responsible for the protection of British interests at home and around the World. 95% of all world trade passes through the high seas and every year Britain imports £524 billion worth of goods. The RN takes an active part in the protection of British Shipping. Around the United Kingdom the RN protects vital fishing stocks by monitoring fishing activities in our waters. We recruit throughout the year, so please ignore Key Dates

https://www.royalnavy.mod.uk/careers (opens in new tab)

After this apprenticeship

You’ll start your naval career as an Able Rate. With experience and further training, you could be promoted to Leading Hand and beyond

If you show the right commitment, skills and academic ability, you could become a Commissioned Officer. Members of the Royal Navy are promoted on merit. Work hard and you can rise through the ranks

Ask a question

The contact for this apprenticeship is:

ROYAL NAVY

The reference code for this apprenticeship is VAC1000255404.

Apply now

Closes on Monday 1 June 2026

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