Placement Student - Data Analyst

We are looking for an enthusiastic Data Analyst student to join our team specializing in Product Lifestyle Management for our Power Systems Business Unit in Sandwich, Kent, UK. During your placement with us, you will learn how a major global organization operates, gaining the tools and exposure you will need to become an expert in the industry.

This role is available to candidates who qualify for a placement year and will commence Summer 2027 The requirements are to be onsite for 3 days per week so you will need to be able to travel or relocate to the location on your own behalf.

In this role, you will make an impact in the following ways:

• Assist in requirements gathering: Work with different business stakeholders (engineers, project managers, Product Lifecyle Management (PLM) IT and Corporate IT) to understand their needs for the PLM system.
• Analyze PLM: Work with large datasets from the PLM system to identify trends, such as common design changes, product component reuse, or bottlenecks in the product development process.
• Conducting research on new technologies, tools, or best practices to inform the solution design
• Supporting the creation of design documents, specifications, or technical diagrams that outline the solution's architecture.
• Writing and testing code or configuring software components under the guidance of a senior team member
• Design and implement innovative solutions in collaboration with the team and present the final outcome to the customer.

To be successful in this role you will need the following:

• Studying towards a STEM related degree. Computer science, data engineering and Software engineering are most desirable but not essential.
• Communication Skills: The ability to articulate complex technical ideas clearly and effectively to both technical and non-technical audiences.
• Knowledge in Computer Science, Software applications and Product Lifecycle Management is beneficial.
• Understanding the Data Bricks will be very helpful and Interested in Big Data Analysis

Closing Date

12th November 2026