Level 3 Data Technician Apprenticeship

Data for Smarter Work Programme

Build practical data, AI and workplace capability to improve data quality, support decisions and strengthen smarter ways of working.

Level 3
Level 3

Data Technician Apprenticeship

Duration
Duration
12 months + end point assessment
Qualification outcomes
Qualification outcomes
Level 3 Data Technician Apprenticeship
+ Microsoft Azure AI Fundamentals certification

 

Audience
Audience

From junior data roles and support roles upwards

Funding
Funding

Fully fundable via the Apprenticeship Levy - funding band £12,000

Time commitment
Time commitment
Approx. 4 hours per week protected learning time

Programme overview

Delivered through the Level 3 Data Technician Apprenticeship, the programme develops practical data, AI and workplace capability from junior data roles upwards while strengthening communication, judgement and responsible handling of data.

The programme helps professionals improve the way work gets done by collecting, preparing, checking and communicating data confidently, responsibly and with measurable value. It includes a built-in professional practice layer so participants not only complete data tasks accurately, but also communicate clearly, manage risk, support decisions and improve ways of working over time. 

Skills and capabilities developed

AI data literacy
Data collection
Data preparation
Data quality
Data visualisation
Communication
Judgement
Data governance
Stakeholder support
Continuous improvement

Evidence & outcomes

Our programmes deliver measurable improvements in data capability, human-centred management capability and organisational performance.

FTL-Microsft

Microsoft AI Certification Included

Microsoft Azure AI Fundamentals included

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Ofsted rated "good"

With 53% of participants promoted during or after the programme

award

100%

Participants report improved data and management capability
award

85%

Distinction rate across programmes, and 100% pass rate

Programme positioning

Who is this
programme for?

From junior data roles and support roles upwards, this programme is for employees responsible for collecting, preparing, checking or communicating data to support everyday work and better decisions.

The role applies broadly across teams, functions and sectors. Typical job titles include Data support analyst, Data technician, Junior data analyst and Junior information analyst. 

Data and reporting roles
• Data support analysts
• Data technicians
• Junior data analysts
• Junior information analysts

Business and operational roles
• Junior MI or reporting roles
• Operations support roles using data
• Performance support roles
• Data administration roles

Service and coordination roles
• Customer or service support roles
• Team support roles using data
• Workflow or reporting support roles
• Operational coordination roles

Functional and support roles
• Junior finance data roles
• Junior people data roles
• Business intelligence support roles
• Data handling roles across teams

Where this
programme fits

This programme builds the foundational data, AI and human-centred capability organisations increasingly rely on to improve data quality, support decisions and strengthen everyday performance.

It forms part of Future Talent Learning’s broader approach to building human, management and AI capability across the workforce.


Core data capability pathway

Supports better data quality and everyday decisions

Strengthens communication, judgement and trust

Builds confidence using AI in data tasks

Progression route into higher-level data and insight roles

Capabilities developed

Participants strengthen practical data, AI and human-centred capability required to make data more reliable, more usable and more valuable to the organisation. 


AI capability - Using AI safely and effectively in everyday data tasks

Data capability – Collecting, preparing, validating and presenting data

Human capability - Communication, consistency and sound judgement

Management capability – Planning work, meeting deadlines and supporting decisions

Collaboration capability – Working with colleagues and stakeholders clearly

Transformation capability – Improving standards, reducing duplication and embedding better practice

Organisational outcomes

Organisations typically use this programme to strengthen data capability from junior roles upwards and improve how data is collected, checked, shared and used in everyday work.

Better quality and more reliable datasets

Stronger compliance and safer data handling

Clearer communication of findings and issues

More effective support for decisions and improvement

Improved data standards and consistency over time

Why this programme?

Our programme helps organisations improve the way work gets done by making data more accurate, more usable and easier to act on.

It develops the capability to collect, prepare, check and communicate data confidently, alongside the management and human-centred skills needed to build trust, support decisions and improve performance.

Levy-funded data capability

AI-enabled learning platform

Supported by Microsoft with AI certification

Built-in professional practice layer

Time-efficient:
learning fits the working week

The real constraint with professional development is rarely funding — it is time.

Our programmes are designed to work with the flow of real work, not compete with it.

Participants typically commit around four hours per week, combining structured learning, coaching and applied missions directly linked to their role.

This ensures development strengthens day-to-day performance while building capability for the future.

 

12 month programme overview

Structured curriculum missions are combined with live workshops and peer learning so participants build capability progressively through real work. For more detail download the programme prospectus.

Curriculum missions

The programme is structured around 12 practical monthly missions linked to real data, quality and workflow challenges.
01

Find and understand data

Identify sources, types and storage formats
02

Extract and format data

Create clean datasets using agreed standards
03

Protect data and use it responsibly

Apply secure handling, anonymisation and good judgement
04

Check and improve data quality

Validate, fix errors and improve reliability
05

Combine and reconcile data

Join sources and resolve differences carefully
06

Document and audit the data

Create traceability, assumptions and audit trail
07

Summarise and explore the data

Filter, sort and identify useful patterns
08

Visualise what matters

Use tables, charts and dashboards clearly
09

Forecast and assess future scenarios

Explore scenarios and interpret results carefully
10

Share data safely and effectively

Store, manage and distribute data compliantly
11

Support decisions and improvement

Translate findings into actions and next steps
12

Embed quality & continuous improvement

Improve standards and maintain consistency

Live learning events

Live learning workshops allow participants to practise new approaches, discuss real data and insight challenges and deepen understanding through guided discussion.
01

How to find the right data sources

Identify the most relevant and reliable inputs
02

Understanding data types and formats

Work confidently with different data structures
03

How to extract and structure data

Create usable datasets for analysis and review
04

How to format datasets clearly

Apply standards that improve consistency and usability
05

How to handle data securely

Protect data and work responsibly
06

GDPR and anonymisation in practice

Use good judgement with sensitive data
07

How to improve data quality

Reduce errors and strengthen trust in outputs
08

How to combine datasets safely

Join sources and maintain accuracy
09

How to check and validate data

Cross-check outputs and spot faults early
10

How to use spreadsheets for analysis

Use practical spreadsheet tools with confidence
11

How to build clear tables and charts

Present the right view for the audience
12

How to use AI safely for data tasks

Use AI responsibly to support everyday data work
13

How to manage stakeholders

Map interests and build alignment early
14

How to frame problems

Define the right question before analysing
15

How to present with visual impact

Make charts and findings easier to understand
16

How to influence with data

Use insight to shape conversations and decisions
17

Leading change

Support teams through change and organisational transformation
18

Collaboration

Work effectively across operational, digital and technical teams.
19

Problem solving

Use structured thinking to diagnose and solve complex problems
20

Stakeholder management

Align stakeholders around automation priorities and improvement goals.

Live peer study groups

Monthly coach-facilitated sessions provide a structured space to exchange ideas, share challenges and explore how learning can be applied in real organisational contexts.
01

How clean is ‘clean enough’ when the deadline is tight?

Balance quality, pace and practical needs
02

If two data sources disagree, which one do you trust — and why?

Compare evidence and explain your judgement
03

When should you anonymise data — and how much is enough?

Apply sound judgement to privacy and risk
04

How do you explain data issues without sounding defensive?

Communicate clearly while protecting trust
05

What’s the best way to challenge a request that isn’t GDPR-safe?

Raise concerns confidently and constructively
06

When is a chart useful — and when does it just create noise?

Choose visuals that actually help others act
07

How do you keep an audit trail without creating admin overload?

Balance compliance, traceability and practicality
08

What’s the simplest analysis that still helps someone act?

Focus on usefulness rather than over-work
09

How do you make data more usable for non-technical colleagues?

Adapt communication for different audiences
10

When priorities change, how do you re-scope cleanly?

Protect value while adjusting the work
11

How do you improve standards without slowing everyone down?

Balance consistency, pace and everyday practicality
12

How do you make better data habits stick?

Support follow-through, trust and continuous improvement

Weekly delivery model

Approx. 4 hours of protected learning time per week One of the most time-efficient delivery models.

Structured learning: approx. 4 hours per week

50%

AI-enabled learning + human coaching + interactive workshops

Participants build capability through a blend of:

• self-paced learning modules
• interactive live workshops
• guided exploration using AI learning tools
• peer study groups and coaching support.

These sessions introduce practical frameworks, tools and approaches that can be applied immediately at work.

Applied learning in the workplace: approx. 4 hours per week

50%

Applied & project-based learning

Participants apply learning directly to real workplace challenges through monthly missions and work-based data and insight tasks. Learning strengthens existing work.

This ensures development is:
• immediately relevant
• visible to the organisation with measurable productivity improvements
• embedded in day-to-day performance

The FTL learning experience

Development is designed around how adults learn most effectively at work — through applied practice, reflection, coaching and collaboration.
Find out more

Real workplace challenges drive learning.

Participants apply new skills directly to their role through structured monthly missions linked to real organisational priorities.

FTL-Applied-learning-missions
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An outstanding programme to accelerate the development of future leaders. — Roger Minton, Head of Leadership, Anglo American
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FTL’s highly customised programme has become the core of our management development strategy. The FTL team are slick, knowledgeable, responsive and a pleasure to work with. - Nick Dormor, Senior Learning Specialist, Babcock
FTL-Quote-Ofsted
FTL provides top-tier, highly engaging, innovative and effective methods of learning, leading to high success rates and impact that line managers can observe. — Ofsted, Sept 2024

Frequently asked questions — Level 3 Data Technician Apprenticeship

See our full FAQs page for more information or contact us if you have any questions.
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Speak to our team

Get in touch to explore how this programme could support your workforce development priorities and strengthen foundational data, AI and workplace capability across your organisation.

We’ll get back to you within one working day.

 
 
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