Process Control & Data Engineer (f/m/d) - Hybrid

About the Role

We are looking for an experienced Process Control & Data Engineer to join our technical team in specialty cable and assembly manufacturing in Pleinfeld, Germany, to advance digitization and shape how process and product data is utilized for high-performance cable solutions. You will join during a time of significant local growth, with the opportunity to contribute through solutions that improve efficiency, effectiveness, and product quality while helping shape the site’s future digital capabilities.

In this role, you will assess how digital systems can be applied broadly and effectively in real-world manufacturing environments and drive their implementation. The role combines system ownership with practical application, enabling you to influence how data is captured, structured, and used to strengthen process control, improve shop-floor performance, and support broader digitization efforts, including quality commitments, cost reduction, and future AI-enabled engineering. Success in this role will require close collaboration with engineering, production, IT, quality, and project teams.

Responsibilities

• Define and structure process and product data for key manufacturing areas to enable stronger process control and data-driven decision-making
• Implement statistical process control methods to improve process stability, detect variation, and support continuous improvement
• Own and improve manufacturing data systems to ensure reliable data capture, availability, and usability for operational teams
• Develop practical solutions to capture relevant equipment, operator, and process data from shop-floor operations
• Build and enhance KPI dashboards and related infrastructure that translate complex manufacturing data into clear insights for cross-functional audiences
• Set up and maintain business processes in partnership with engineering, production, quality, and IT teams to turn data insights into improvements in performance, efficiency, and product quality
• Strengthen data traceability to support root cause analysis, quality compliance, and customer audit readiness
• Translate customer-specific quality and documentation requirements into practical process control and data solutions
• Contribute to the site’s digital roadmap by identifying scalable opportunities and supporting implementation priorities
• Lead technical projects from concept through implementation in collaboration with cross-functional stakeholders and teams

Required Qualifications

• Bachelor’s degree or higher in a relevant field of study (STEM disciplines)
• Minimum of 5 years of professional experience within a complex manufacturing environment
• Working knowledge of statistical methods, data analysis, and process optimization methods used to improve manufacturing performance
• Experience translating complex data from multiple sources into clear insights, summaries, or dashboards for cross-functional audiences
• Proven ability to analyze process and product data and drive measurable improvements in manufacturing performance, efficiency, or quality
• Self-directed and analytical working style with the ability to manage multiple priorities independently
• Ability to quickly learn new technologies, processes, and subject matter in a changing manufacturing environment
• Strong communication skills with the ability to collaborate effectively across engineering, production, quality, and IT teams
• Fluent in German and English, both written and spoken
• Willingness and ability to travel up to 10 %

Desired Qualifications

• Professional engineering experience in the field of cable, cable assembly or printed circuit board production
• Advanced knowledge of statistical methods, data analysis and process optimization methodologies
• Experience working with manufacturing execution or enterprise resource planning systems in regulated or quality-driven manufacturing environments
• Ability to translate systems thinking into scalable digital manufacturing solutions that strengthen site-wide process control, data visibility, and continuous improvement