Marketing Data Analysis Apprentice

51DEGREES.MOBI LTD
Reading, Berkshire

Summary

An opportunity for a Marketing Data Analysis Apprentice based in Central Reading, with hybrid options post‑probation. The apprentice will enrol onto a Level 3 programme with progression opportunities. The role supports digital marketing, reporting, analytics and optimisation.

Wage

£18,000 a year

Training course
Data technician (level 3)

Hours
Monday to Friday, 9am - 5.30pm. First 3-months are 100% office based, then hybrid following this. It will then be 3-days in the office, and 2-days at home.

37 hours 30 minutes a week

Start date

Wednesday 6 May 2026

Duration

1 year 5 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

  • Resolve 404 errors and ensure correct redirections
  • Maintain consistent UTM parameters
  • Review and update open‑source package pages
  • Monitor Core Web Vitals and report findings
  • Track competitor updates and support fortnightly reporting
  • Prepare initial drafts of online performance reports
  • Complete delegated tasks from the Marketing Lead

Where you'll work

3RD FLOOR
DAVIDSON HOUSE
THE FORBURY
READING
RG1 3EU

Training

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

Training provider

QA LIMITED

Training course

Data technician (level 3)

What you'll learn

Course contents

  • Select and migrate data from already identified sources.
  • Format and save datasets.
  • Summarise, analyse and explain gathered data.
  • Combine data sets from multiple sources and present in format appropriate to the task.
  • Use tools and/or apply basic statistical methods to identify trends and patterns in data.
  • Identify faults and cleanse data to improve data quality, for example identifying gaps, duplicate entries, outliers and unusual variances, including cross-checking across data elements or between data sources.
  • Audit data results for maintenance of data quality, reviewing a data set once all sources are combined, to ensure accuracy, completeness, consistency and traceability from original data.
  • Demonstrate the different ways of communicating meaning from data in line with audience requirements.
  • Produce clear and consistent documentation of the data provided to others and of actions completed. Where appropriate or mandated by the working context, this documentation should use standard organisational templates.
  • Store, manage and distribute data in compliance with organisational, national, sector specific standards and or legislation.
  • Considers sustainability and ways to reduce impact. For example, using cloud storage, sharing links to files, avoid storing multiple versions of files, and reducing the use of physical handouts of documentation.
  • Parse data against standard formats, and test and assess confidence in the data and its integrity.
  • Operate collaboratively in a working context that accounts for, and takes advantage of, the roles, skills and activities of others, especially those interacting with the same data sets or working towards a common goal.
  • Prioritise own activities within the context of the duties to be performed, taking account of any known or expected impact on others.
  • Follows equity, diversity and inclusion policies in the organisation for a common goal.
  • Demonstrate the ability to use different tools and methods to formulate and utilise effective prompts to research, apply, and evaluate data transformation techniques.
  • Select and migrate data from already identified sources.
  • Format and save datasets.
  • Summarise, analyse and explain gathered data.
  • Combine data sets from multiple sources and present in format appropriate to the task.
  • Use tools and/or apply basic statistical methods to identify trends and patterns in data.
  • Identify faults and cleanse data to improve data quality, for example identifying gaps, duplicate entries, outliers and unusual variances, including cross-checking across data elements or between data sources.
  • Audit data results for maintenance of data quality, reviewing a data set once all sources are combined, to ensure accuracy, completeness, consistency and traceability from original data.
  • Demonstrate the different ways of communicating meaning from data in line with audience requirements.
  • Produce clear and consistent documentation of the data provided to others and of actions completed. Where appropriate or mandated by the working context, this documentation should use standard organisational templates.
  • Store, manage and distribute data in compliance with organisational, national, sector specific standards and or legislation.
  • Considers sustainability and ways to reduce impact. For example, using cloud storage, sharing links to files, avoid storing multiple versions of files, and reducing the use of physical handouts of documentation.
  • Parse data against standard formats, and test and assess confidence in the data and its integrity.
  • Operate collaboratively in a working context that accounts for, and takes advantage of, the roles, skills and activities of others, especially those interacting with the same data sets or working towards a common goal.
  • Prioritise own activities within the context of the duties to be performed, taking account of any known or expected impact on others.
  • Follows equity, diversity and inclusion policies in the organisation for a common goal.
  • Demonstrate the ability to use different tools and methods to formulate and utilise effective prompts to research, apply, and evaluate data transformation techniques.

Training schedule

Why choose our Data Essentials apprenticeship?

QA’s Data Essentials Level 3 apprenticeship can support your business to be more productive with data and adapt to a modern-day workplace. Data available to organisations is increasing at scale. How your business leverages it is essential to successful transformation and continued growth.

QA's Data Essentials Level 3 apprentice will learn to:

  • Source, format and present data securely, using Microsoft Excel, Power BI and SQL.
  • Analyse structured and unstructured data to support business outcomes
  • Blend data from multiple sources as directed
  • Communicate outcomes appropriate to the audience
  • Apply legal and ethical principles when manipulating data

QA’s Data Essential Level 3 apprenticeship programme enables your organisation to:

  • Build the capabilities you need throughout your organisation to collect, study, organise and present data, increasing digital adoption and the provision of intelligent and valuable business insights
  • Create and develop analysts for the modern workplace by reskilling your existing talent or hiring new entry-level talent. QA’s programmes, partnerships and recruitment capability enable us to tailor a solution that works for your business
  • Provide training that acts as a standalone solution or as part of a wider academy/programme to an array of business functions

Tools and technologies learned: Apprentices will learn to use Microsoft Excel and Power BI.

Requirements

Essential qualifications

GCSE in:

  • 3 of any subject (grade 4+ (A* - C))
  • Maths & English (grade 3+ (D 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
  • Attention to detail
  • Problem solving skills
  • Analytical skills
Posted 2026-03-30

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