Data Technician Apprentice

As a Data Technician Apprentice, you will support the collection, organisation, analysis, and reporting of data to help the business make informed decisions. You will work alongside experienced colleagues who will provide training and support throughout your apprenticeship.

What you'll do at work:

• Collecting, validating, and maintaining accurate data.
• Updating and managing databases and spreadsheets.
• Producing reports, dashboards, and data summaries.
• Identifying trends and patterns within data.
• Assisting with data quality checks and ensuring information is accurate.
• Supporting different departments with data requests.
• Learning how to use industry-standard software and reporting tools.
• Maintaining confidentiality and handling data in line with GDPR requirements.
• Working as part of a team while managing your own workload.

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

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.
• Consider 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.