Summary
The Data Analyst will be responsible for collecting, processing, and analysing data to support strategic decision-making & planning across the business.
Wage
£14,918.80 for your first year, then could increase depending on your age
National Minimum Wage rate for apprentices
Training course
Data analyst (level 4)
Hours
Monday - Thursday 07:30am - 16:15. Friday 07:30am - 12.45pm.
38 hours 15 minutes a week
Start date
Wednesday 20 August 2025
Duration
2 years
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
* Analyse large datasets to identify trends, patterns, and insights
* Develop and maintain dashboards and reports using tools like Power BI
* Perform data cleaning, transformation, and validation to ensure accuracy and quality
* Collaborate with stakeholders to gather requirements and deliver data solutions
* Conduct A/B tests and statistical analysis to inform business decisions
* Monitor key performance indicators (KPIs) and provide regular performance reports
* Work with data engineering teams to improve data pipelines and data architecture
* Present findings to stakeholders through visualisations and presentations
Where you'll work
59-61 EAST PARADE
ILKLEY
LS29 8JP
Training
Apprenticeships include time away from working for specialist training. You’ll study to gain professional knowledge and skills.
Training provider
BRADFORD COLLEGE
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
* All work uploaded to Aptem
* Monthly college release days (online or face to face)
Requirements
Essential qualifications
GCSE in:
* English (grade C or 4)
* Maths (grade C or 4)
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
* Problem solving skills
* Administrative skills
* Analytical skills
* Logical
* Team working
* Creative
* Initiative