Data Engineer Apprentice

Coventry City Council

Coventry (CV1 2FL)

Closes in 19 days (Sunday 31 May 2026)

Posted on 12 May 2026

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Summary

As a Data Engineer Apprentice, you’ll learn how data is moved, prepared, and managed behind the scenes so that analysts, services, and leaders can rely on accurate, timely information to make better decisions.

Wage

£20,932 a year

Check minimum wage rates (opens in new tab)

Training course
Data technician (level 3)
Hours
Monday - Friday, 9.00am - 5.00pm

37 hours a week

Start date

Monday 7 September 2026

Duration

2 years 6 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 ingestion and preparation of data from council systems into our corporate data platforms
  • Help build and maintain data pipelines and structured datasets
  • Assist with monitoring scheduled and overnight data processes
  • Log and manage data‑related incidents and requests through our service management system, working to agreed service levels
  • Support data analysts by ensuring datasets are reliable, well‑structured, and fit for reporting and analysis
  • Help maintain documentation so data flows and processes are clearly understood
  • Provide limited operational support for data integrations between core systems (such as payments into the financial system), acting as cover when required
  • Learn and apply data governance, security, and data protection principles
  • Complete an approved apprenticeship programme alongside your day‑to‑day role

Where you'll work

Friargate
Station Square
Coventry
CV1 2FL

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)

Understanding apprenticeship levels (opens in new tab)

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

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

Requirements

Desirable qualifications

GCSE in:

  • English (grade C/4)
  • Maths (grade C/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
  • Customer care skills
  • Problem solving skills
  • Presentation skills
  • Administrative skills
  • Number skills
  • Analytical skills
  • Logical
  • Team working
  • Creative
  • Initiative
  • Non judgemental
  • Patience

About this employer

Coventry is a city that is changing fast and we’re looking for skilled people to join our team and help take us into a bright new future. We are a city that is going places with an inspiring, world-famous history and exciting times ahead. A great place to live and work and it’s getting even better - and having the right infrastructure is vital. We particularly welcome applicants from minority ethnic backgrounds, applicants who have a disability and applicants who are from the LGBTQ+ community to apply for our senior leadership roles. That’s why we are looking for people who are passionate, dedicated people who, like us, are determined to make real, positive change to Coventry.

After this apprenticeship

  • A permanent role within the team (subject to funding) 

Ask a question

The contact for this apprenticeship is:

QA LIMITED

The reference code for this apprenticeship is VAC2000031303.

Apply now

Closes in 19 days (Sunday 31 May 2026)

After signing in, you’ll apply for this apprenticeship on the company's website.