Level 3 Apprentice Data Technician

Are you interested in data and technology? Join Sandwell Council's School Attendance Support Service as a Level 3 Data Technician Apprentice, where you'll gain hands-on experience collecting, managing and analysing data, producing reports and dashboards, and supporting service improvements while earning a nationally recognised qualification.

Wage: £15,392 for your first year, then could increase depending on your age, National Minimum Wage rate for apprentices.

Training course: Data technician (level 3)

Hours: Monday to Friday - between the hours of 8am - 5pm, 37 hours a week

Start date: Monday 19 October 2026

Duration: 2 years

Positions available: 1

What you'll do at work

Your main duties and responsibilities will include:

• Support the production of reports and dashboards to monitor service performance.
• Collect, check and input performance and service data accurately.
• Learn to use council systems and software to retrieve and analyse information.
• Assist in maintaining accurate, up-to-date and secure data records.
• Help document processes and maintain records of data and reporting activities.
• Work with colleagues across different teams to share information and improve data quality.
• Support projects and initiatives that contribute to service improvement.
• Develop an understanding of data protection, information governance and confidentiality requirements.
• Participate in team meetings and training activities.
• Promote equality, diversity and inclusion in all aspects of your work.
• Comply with health and safety policies and procedures at all times.

Where you'll work

Freeth Street
Oldbury
B69 3DB

Training provider: QA LIMITED

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.