Data Analyst Apprentice

Summary

The Data Analyst will play a key role, working with the business teams to plan and deliver these new reporting capabilities. This will include gathering requirements, working with the teams to understand and access the date , building, testing and improving reports. Additionally the Data Analyst will support other colleagues.

Wage

£20,000 a year

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Training course

Data analyst (level 4)

Hours

Monday to Friday.

37 hours 30 minutes a week

Start date

Wednesday 20 August 2025

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

· Support the IT Manager in planning and execution of the new data / reporting strategy and improvement initiatives.

· Responsible for the delivery of new reports and dashboards across the Credit Union.

· Develop and implement databases, data collection systems and data engineering solutions that optimise reporting efficiency and clarity.

· Acquire data from primary or secondary data sources and maintain databases/data lakes.

· Interpret data, analyse results using statistical techniques and provide ongoing reports.

· Identify, analyse, and interpret trends or patterns in complex data sets.

· Filter and “clean” data by reviewing raw data, reports, and performance indicators to locate and correct code problems.

· Work with management to prioritise business and information needs.

· Locate and define new process improvement opportunities.

Where you'll work

SLATER HOUSE
OAKFIELD ROAD
CHEADLE ROYAL BUSINESS PARK
CHEADLE
SK8 3GX

Training

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

College or training organisation

NOWSKILLS LIMITED

Your training course

Data analyst (level 4)

Understanding apprenticeship levels (opens in new tab)

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

Your training plan

This training plan has not been finalised. Check with this employer if you’ll need to travel to a college or training location for this apprenticeship.

More training information

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

Requirements

Let the company know about other relevant qualifications and industry experience you have. They can adjust the apprenticeship to reflect what you already know.

Skills

Communication skills
IT skills
Organisation skills
Problem solving skills
Analytical skills
Team working
Initiative
Skills in Excel
Experienced in data
understanding of data concept
knowledge of SQL
Programming languages
Microsoft Excel

Other requirements

A full UK driving license is desirable. A good level of maths.

About this company

No1 CopperPot Credit Union is a not-for-profit organisation, exclusively for the Police community and owned by its members. No1 CopperPot makes it simple to save, provides affordable loans and can help a member buy or remortgage their home. Here’s why you’ll love working with us and what we need from you.

http://www.no1copperpot.com (opens in new tab)

After this apprenticeship

This role could grow into a full-time position after your apprenticeship ends.

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