Data Analyst Apprentice in United Kingdom

Summary

As a Data Analyst Apprentice, you will work with a range of business data to identify trends, produce meaningful insights and support informed decision-making. Working alongside experienced professionals, you will gain practical experience using data analysis techniques, reporting tools and business intelligence software.

Wage

£16,000 a year

Training course

Data analyst (level 4)

Hours

Monday to Friday, full-time position. Shifts to be confirmed.

37 hours 30 minutes a week

Start date

Monday 7 December 2026

Duration

1 year 8 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

• Collecting, validating and analysing data from multiple sources
• Creating and maintaining reports, dashboards and visualisations
• Identifying trends, patterns and opportunities within business data
• Supporting business decisions by presenting accurate data insights
• Working with stakeholders to understand reporting requirements
• Ensuring data accuracy, quality and integrity
• Maintaining confidentiality and handling data in accordance with GDPR

Where you'll work

Bolton
Greater Manchester
BL1 1AA

Training

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

Training provider

NOWSKILLS LIMITED

Training course

Data analyst (level 4)

What you'll learn

• 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

Data Analyst Level 4.

More training information

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

Requirements

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
• Team working

Other requirements

• Has a genuine interest in data analysis and using data to solve business problems
• Has a good understanding of data, spreadsheets and analytical techniques
• Is confident using Microsoft Excel, including formulas and data manipulation
• Has strong numerical, analytical and problem-solving skills
• Can interpret data and present findings in a clear and meaningful way
• Has excellent attention to detail and a methodical approach to work
• Is organised and able to manage multiple priorities effectively
• Has an interest in reporting tools such as Power BI, SQL or similar data analysis software