Data Analyst Apprentice (Level 4)

Summary

We are seeking a curious and analytically minded individual to join our team as a Data Analyst Apprentice (Level 4). Gain hands-on experience with real data, visualisation, statistical analysis, and data engineering while completing a nationally recognised Level 4 Data Analysis qualification.

Wage

£16,000 a year

The pay may be negotiated and may rise after a probation period has been successfully completed

Training course

Data analyst (level 4)

Hours

Monday to Friday, 9.00am to 5.00pm.

37 hours 30 minutes a week

Start date

Tuesday 25 August 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

• Collect, clean, and validate data from multiple internal and external sources
• Analyse and interpret complex data sets to identify trends, patterns, and actionable insights
• Build and maintain interactive dashboards and reports using Power BI
• Write and optimise SQL queries to extract and manipulate data from relational databases
• Use Python and/or R to perform statistical analysis, automate processes, and build analytical pipelines
• Work with big data tools and platforms to handle large-scale datasets
• Present findings clearly to both technical and non-technical audiences
• Collaborate with stakeholders to understand data requirements and translate them into analytical outputs
• Maintain data quality, documentation, and governance standards

Where you'll work

You can select which locations you want to apply for in your application on Find an apprenticeship.

This apprenticeship is available in these locations:

• Town Hall, 1 Town Square, Barking, IG11 7LU
• Gun Wharf, Dock Road, Chatham, ME4 4TR
• King Street, London, W6 9JT
• Council House, Manor Square, Solihull, B91 3QB

Training

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

Training provider

VELOCITY 1ST LIMITED

Training course

Data analyst (level 4)

What you'll learn

Course contents

• Use data systems securely to meet requirements and in line with organisational procedures and legislation including principles of Privacy by Design
• implement the stages of the data analysis lifecycle
• apply principles of data classification within data analysis activity
• analyse data sets taking account of different data structures and database designs
• assess the impact on user experience and domain context on data analysis activity
• identify and escalate quality risks in data analysis with suggested mitigation or resolutions as appropriate
• undertake customer requirements analysis and implement findings in data analytics planning and outputs
• identify data sources and the risks and challenges to combination within data analysis activity
• apply organizational architecture requirements to data analysis activities
• apply statistical methodologies to data analysis tasks
• apply predictive analytics in the collation and use of data
• collaborate and communicate with a range of internal and external stakeholders using appropriate styles and behaviours to suit the audience
• use a range of analytical techniques such as data mining, time series forecasting and modelling techniques to identify and predict trends and patterns in data
• collate and interpret qualitative and quantitative data and convert into infographics, reports, tables, dashboards and graphs
• select and apply the most appropriate data tools to achieve the optimum outcome
• Use data systems securely to meet requirements and in line with organisational procedures and legislation including principles of Privacy by Design
• implement the stages of the data analysis lifecycle
• apply principles of data classification within data analysis activity
• analyse data sets taking account of different data structures and database designs
• assess the impact on user experience and domain context on data analysis activity
• identify and escalate quality risks in data analysis with suggested mitigation or resolutions as appropriate
• undertake customer requirements analysis and implement findings in data analytics planning and outputs
• identify data sources and the risks and challenges to combination within data analysis activity
• apply organizational architecture requirements to data analysis activities
• apply statistical methodologies to data analysis tasks
• apply predictive analytics in the collation and use of data
• collaborate and communicate with a range of internal and external stakeholders using appropriate styles and behaviours to suit the audience
• use a range of analytical techniques such as data mining, time series forecasting and modelling techniques to identify and predict trends and patterns in data
• collate and interpret qualitative and quantitative data and convert into infographics, reports, tables, dashboards and graphs
• select and apply the most appropriate data tools to achieve the optimum outcome

Training schedule

Velocity apprenticeship training programmes are delivered virtually by our fully qualified and industry experienced training team. Using their expert knowledge, they will provide the skills necessary to succeed in the workplace and to expand future career prospects.

Throughout the apprenticeship learners receive coaching, help and guidance from a dedicated team who are there to ensure they get the most from their programme.

Requirements

Essential qualifications

GCSE in:

• English (grade 4/C or above (or equivalent))
• Maths (grade 4/C or above (or equivalent))

Desirable qualifications

Level 3 qualification (A Level,BTEC or equivalent) in:

Mathematics or a related subject (grade Pass or above)

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
• Presentation skills
• Administrative skills
• Analytical skills
• Logical
• Team working
• Creative
• Initiative
• Patience