Manufacturing Process Engineer – Sensors & Cartidges

Coopers Group; Rotkreuz; Vor Ort; CHF 110.000 - 150.000; Vollzeit

Zusammenfassung

Coopers Group is seeking an Engineer to identify gaps in automated production and implement robust improvements. You will analyze processes, monitor KPIs, and apply DoE methods across lab and manufacturing settings to support scale-up.

Collaboration with shop-floor teams and cross-functional engineers is essential, along with strong documentation in a GxP environment. You should have a background in engineering or physics, experience with Python or R, and fluency in English and German.

Qualifikationen

• Experience with automated production and robotics on the shop floor.
• Ability to implement DoE in lab and manufacturing environments.
• Strong documentation and GxP mindset.
• Proficiency in Python or R for data analysis.
• Fluent in English and German (B2+).
• Hepatitis vaccination required for lab access.

Aufgaben

• Identify & solve gaps in production processes to uncover limitations, risks, and root causes.
• Drive improvements via digital tools, new technologies, equipment upgrades, and workflow enhancements.
• Monitor production KPIs, detect deviations with control loops, and implement in-process quality controls.
• Plan and execute DoE across lab and manufacturing environments to support scale-up.
• Collaborate with shop-floor technicians and cross-functional engineers to align practical details with solutions.
• Create and maintain robust process documentation and change records per GxP standards.

Kenntnisse

Python

R

Data analysis

GxP documentation

Shop-floor collaboration

English (B2+)

German (B2+)

Ausbildung

Engineering or Physics background

Tools

SQL

Snowflake

DoE

Jobbeschreibung

Your responsibilities:

• Identify & Solve Gaps: Analyze production processes to uncover limitations, root causes, and risks in process robustness, control strategy, and equipment
• Drive Improvements: Develop and implement actionable solutions—ranging from digital tools and new technologies to equipment upgrades and workflow enhancements
• Control Strategies & Data: Monitor production KPIs, detect early deviations using control loops, and implement impactful in-process quality controls
• Testing & Ramp-up: Plan and execute Design of Experiments (DoE) across lab and manufacturing environments, supporting the scale-up of new production lines
  Shop-Floor Collaboration: Partner closely with shop-floor teams, technicians, and cross-functional stakeholders to align practical reality with engineering solutions
• Compliance & Documentation: Create and maintain robust process documentation, change records, and work instructions in line with GxP standards

Your background:

• You bring educational background in Engineering (Mechanical, Mechatronics, Automation, Electrical, Micro/Precision Engineering), Physics, Materials Science, or equivalent practical experience
• You bring technical experience and a practical background in complex automated production, robotics, high-precision assembly, dispensing, joining technologies, or delicate component handling
• You bring a shop-floor and GxP mindset: pragmatic and approachable on the production floor, with a clear commitment to structured technical documentation within a GxP environment (training provided)
• You bring data and digital skills, including practical ability in at least one programming language (e.g., Python, R) or working with modern digital tools/AI workflows
• You bring strong interpersonal and collaboration skills, with an open-minded approach to engage seamlessly with shop-floor technicians, ask probing questions, and clearly convey analytical insights to cross-functional lead engineers
• You bring an agile mindset, with experience or enthusiasm for agile frameworks (Scrum, Kanban, PI planning) and cross-functional collaboration.
• You bring professional fluency in English and German at B2 level or higher.
• Hepatitis vaccination required for laboratory and clean production access.

Nice to Haves:

• Familiarity with continuous improvement / Lean Six Sigma methods (SIPOC, value stream mapping, root-cause toolkits).
• Experience in advanced statistical analysis, database queries (SQL, Snowflake), or digital manufacturing projects.