Data Analyst Apprentice

Summary

We are looking for a passionate Junior Data Analyst. The successful candidate will have a keen eye for detail, a willingness to learn and an understanding of the link between data, insights, and business decisions.

Wage

£18,000 a year

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Training course

Data analyst (level 4)

Hours

Monday - Friday, 9.00am - 5.00pm

37 hours a week

Start date

Monday 21 July 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

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

Arndale House
Chester Road, Stretford
Manchester
M32 9ED

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)

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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

Data Analyst Level 4 (Higher national certificate) Apprenticeship Standard
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
Attention to detail
Organisation skills
Problem solving skills
Analytical skills
Team working

Other requirements

• A good understanding of data concepts, particularly around structured and semi-structured data sets. • Theoretical knowledge of SQL language. Any working experience would be a plus. • Knowledge of at least one programming language. Python, R, Java, C#, etc... • Proficiency in the use of Microsoft Excel. • Experience of Microsoft Power BI would be a plus. • Understanding of ETL platforms would be a plus. • Strong analytical skills with the ability to collect, organise, analyse, and disseminate significant amounts of information with attention to detail and accuracy. • Good level of Maths.

About this company

Standguide have supported individuals and employers for over 30 years. We are a nationwide market leader and have helped over 13,000 people across the UK in the last 12 months to retrain, find new careers or grow their own businesses

http://www.standguide.co.uk (opens in new tab)

After this apprenticeship

The successful candidate, upon completion, may be offered a full-time role

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