Data Analyst - Apprentice

Siemens Energy

Newcastle upon Tyne (NE6 2YL)

Closes in 13 days (Tuesday 14 April 2026)

Posted on 1 April 2026

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Summary

In this 18 month Level 4 Data Analyst Apprenticeship, you will help teams make better decisions by turning data into clear insights. Your day might include gathering information from different sources, cleaning up the data, finding patterns and trends, and sharing what you’ve discovered through easy-to-read reports and dashboards.

Wage

£15,392 for your first year, then could increase depending on your age

National Minimum Wage rate for apprentices

Check minimum wage rates (opens in new tab)

Training course
Data analyst (level 4)
Hours
Monday to Friday, shifts to be confirmed.

37 hours a week

Start date

Tuesday 1 September 2026

Duration

1 year 6 months

Positions available

2

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

  • Work with team members to understand their questions, define what success looks like, and turn their needs into clear tasks.
  • Collect, clean, and change data using tools like Alteryx and Python, then create Power BI reports and dashboards to show trends, risks, and opportunities for improvement.
  • Help teams access the right information at the right time using Alteryx and Mendix, making it easier for everyone to work with data.

Where you'll work

C A Parsons Works
Shields Road
Newcastle upon Tyne
NE6 2YL

Training

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

Training provider

BALTIC TRAINING SERVICES LIMITED

Training course

Data analyst (level 4)

Understanding apprenticeship levels (opens in new tab)

What you'll learn

Course contents
  • Use data systems securely to meet requirements and in line with organisational procedures and legislation including principles of Privacy by Design
  • implement the stages of the data analysis lifecycle
  • apply principles of data classification within data analysis activity
  • analyse data sets taking account of different data structures and database designs
  • assess the impact on user experience and domain context on data analysis activity
  • identify and escalate quality risks in data analysis with suggested mitigation or resolutions as appropriate
  • undertake customer requirements analysis and implement findings in data analytics planning and outputs
  • identify data sources and the risks and challenges to combination within data analysis activity
  • apply organizational architecture requirements to data analysis activities
  • apply statistical methodologies to data analysis tasks
  • apply predictive analytics in the collation and use of data
  • collaborate and communicate with a range of internal and external stakeholders using appropriate styles and behaviours to suit the audience
  • use a range of analytical techniques such as data mining, time series forecasting and modelling techniques to identify and predict trends and patterns in data
  • collate and interpret qualitative and quantitative data and convert into infographics, reports, tables, dashboards and graphs
  • select and apply the most appropriate data tools to achieve the optimum outcome
  • Use data systems securely to meet requirements and in line with organisational procedures and legislation including principles of Privacy by Design
  • implement the stages of the data analysis lifecycle
  • apply principles of data classification within data analysis activity
  • analyse data sets taking account of different data structures and database designs
  • assess the impact on user experience and domain context on data analysis activity
  • identify and escalate quality risks in data analysis with suggested mitigation or resolutions as appropriate
  • undertake customer requirements analysis and implement findings in data analytics planning and outputs
  • identify data sources and the risks and challenges to combination within data analysis activity
  • apply organizational architecture requirements to data analysis activities
  • apply statistical methodologies to data analysis tasks
  • apply predictive analytics in the collation and use of data
  • collaborate and communicate with a range of internal and external stakeholders using appropriate styles and behaviours to suit the audience
  • use a range of analytical techniques such as data mining, time series forecasting and modelling techniques to identify and predict trends and patterns in data
  • collate and interpret qualitative and quantitative data and convert into infographics, reports, tables, dashboards and graphs
  • select and apply the most appropriate data tools to achieve the optimum outcome

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

Essential qualifications

GCSE in:

  • English Language (grade 4/C)
  • Mathematics (grade 4/C)

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
  • Initiative
  • Patience

About this employer

At Siemens Energy, we are more than just an energy technology company. With 100,000 dedicated employees in more than 90 countries, we develop the energy systems of the future, ensuring that the growing energy demand of the global community is met reliably and sustainably. The technologies created in our research departments and factories drive the energy transition and provide the base for one sixth of the world's electricity generation. Our global team is committed to making sustainable, reliable, and affordable energy a reality by pushing the boundaries of what is possible. We uphold a 150-year legacy of innovation that encourages our search for people who will support our focus on decarbonization, new technologies, and energy transformation.

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

Successful completion of this 18 month apprenticeship could lead to a future within Siemens Energy.

Ask a question

The contact for this apprenticeship is:

BALTIC TRAINING SERVICES LIMITED

The reference code for this apprenticeship is VAC2000024547.

Apply now

Closes in 13 days (Tuesday 14 April 2026)

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