Client Data Apprentice

CMS CAMERON MCKENNA NABARRO OLSWANG LLP

London (EC4N 6AF)

Closes in 10 days (Saturday 1 November 2025)

Posted on 20 October 2025


Summary

We are looking for a Client Data Apprentice (eDisclosure) to join our team. As an apprentice, you will assist in the end-to-end process of managing electronic data for legal matters.

Training course
Data technician (level 3)
Hours
Monday to Friday 9.30 a.m. - 5.30 p.m.

35 hours a week

Start date

Monday 1 December 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

  • Assist with receiving, cataloguing, and organising client data for new eDiscovery projects
  • Facilitate the opening of new eDiscovery databases or workspaces in RelativityOne
  • Help set up user accounts in RelativityOne and Microsoft 365
  • Support data processing tasks including de-duplication, filtering, and error resolution
  • Assist with identifying, preserving, and collecting electronic information relevant to cases
  • Support document review preparation, including search query execution and document batching
  • Assist with producing data for disclosure and performing quality checks
  • Maintain records for data volumes, user licences, and project activities
  • Help troubleshoot technical issues and escalate as necessary
  • Contribute to internal documentation and workflow checklists
  • Liaise with legal case teams, project managers, and IT support as needed
  • Engage actively in training opportunities and self-directed learning

Where you'll work

Cannon Place 78 Cannon Street
London
EC4N 6AF

Training

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

Training provider

BPP PROFESSIONAL EDUCATION 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

Data Technician Level 3.

Learning is delivered on the job without formal classroom study or day release. The role includes structured training plans, mentoring from senior team members, and access to online training resources, including RelativityOne modules.

You will have regular progress reviews and support from CMS’s Learning & Development and HR teams. This practical structure ensures that apprentices develop the competencies necessary for future advancement within the eDiscovery team.

Requirements

Essential qualifications

GCSE in:

  • English (grade 6)
  • Maths (grade 6)

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
  • Administrative skills
  • Analytical skills
  • Logical
  • Team working

About this employer

CMS is a Future Facing firm. With 80 offices in 50 countries and 5,000+ lawyers worldwide, we combine deep sector understanding with a global overview, giving us the ability not only to see what's coming, but to shape it. CMS is well equipped to help our clients face the future with confidence. We are driven by technology and readily embrace the possibilities it opens up for developing new and better ways of delivering legal services. Our bold approach to a changing future ensures that we nurture our employees and recruit top talent. We work hard to be a truly client-focused law firm. That means not just understanding the unique challenges of every market sector, but also providing a service that’s tailored to the needs of each client. Our partners are hands-on and work hard to get closer to clients with everything from joint training initiatives and advice surgeries to visits and social events. What’s more, our teams have the ideal balance of personality and industry expertise to suit the varied needs of our clients.

Disability Confident

Disability Confident

A fair proportion of interviews for this apprenticeship will be offered to applicants with a disability or long-term health condition. This includes non-visible disabilities and conditions.

You can choose to be considered for an interview under the Disability Confident scheme. You’ll need to meet the essential requirements to be considered for an interview.

After this apprenticeship

Upon successful completion of the apprenticeship, you will be eligible for consideration for permanent roles such as Client Data Administrator or eDisclosure Consultant. The role offers a structured progression path into more senior positions, with the opportunity to specialise in data analytics, project management, or technical consulting in the legal tech field.

Ask a question

The contact for this apprenticeship is:

CMS CAMERON MCKENNA NABARRO OLSWANG LLP

Darren Howard

Darren.Howard@cms-cmno.com

The reference code for this apprenticeship is VAC1000347276.

Apply now

Closes in 10 days (Saturday 1 November 2025)

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