Overview
Our client, a leading pharmaceutical organization, is seeking a Project Engineer Digitalisation to drive digital transformation within their manufacturing development department. This role focuses on bridging the gap between innovative manufacturing operations and modern digital tools to enhance efficiency and compliance. The project involves taking ownership of the digitalisation track and implementing hands-on solutions for industrial-scale manufacturing.
Responsibilities
* Lead the design and implementation of a digital documentation system to replace paper-based records in production.
* Develop and deploy digital solutions using the Microsoft Power Platform, including Power Apps, Power BI, and Power Automate.
* Scout and pilot AI and digital tools that provide practical value to daily manufacturing operations.
* Engage with stakeholders through interviews and job shadowing to translate operational needs into technical requirements.
* Identify opportunities to digitalise process-related workflows, documentation, and data flows within the manufacturing environment.
* Act as a change agent to coach colleagues and increase digital competencies across the department.
* Apply continuous improvement methods to pilot ideas and deliver quantified results.
Requirements
* You possess a Master’s degree in Bio-Engineering, Industrial Pharmacy, Engineering, Sciences, or Information Technology.
* You have 3+ years of relevant experience in a technical or digital implementation role.
* You bring a strong affinity for digitalization, data, and AI concepts.
* You have experience with the Microsoft Power Platform, with a specific focus on Power Apps.
* You possess knowledge of GMP standards or the ability to quickly adapt to a regulated environment.
* You are proactive, autonomous, and possess excellent communication and interpersonal skills.
* You are fluent in English.
Nice to Haves
* Previous experience in completing an AI-related project.
* Basic programming skills in Python, SQL, or VBA.
* Experience with data analysis and statistics.
#J-18808-Ljbffr