Manufacturing Process Analyst_925393

ITech Consult AG; Zug; On-site; CHF 110,000 - 150,000; Full time

Job summary

ITech Consult AG seeks a Manufacturing Process Analyst / Engineer to optimize complex automated production lines across sensors, cartridges, robotics, and MSAT environments. You will analyze processes, implement improvements, and ensure robust documentation under GxP frameworks.

The role requires hands-on shop-floor experience, programming skills (Python or R), and fluent English and German at B2 level or higher. Swiss manufacturing presence with cross-functional collaboration.

Qualifications

• Engineering degree or equivalent practical experience.
• Experience with complex automated production and robotics.
• Industry exposure in regulated environments is a plus.
• Shop-floor and GxP documentation experience.
• Programming skills (Python or R) or familiarity with digital tools/AI workflows.

Responsibilities

• Identify and solve gaps in GxP production processes and risks.
• Drive improvements across digital tools, new technologies, and equipment upgrades.
• Monitor KPIs, detect deviations, and implement quality controls.
• Plan and run DoE studies and support scale-up of new lines.
• Maintain robust process documentation, change records and work instructions.

Skills

GxP mindset

Python

R

Data analysis

German-English

Education

Engineering degree

Mechatronics background

Tools

Python

R

SQL

Snowflake

Job description

Manufacturing Process Analyst / Engineer: GxP / MSAT / Complex automated production / Sensors & Cartridges / Robotics / Python or R / robust process documentation / English / Deutsch

Tasks & 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

Must Haves:

• 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 industry experience across various sectors (e.g., medical devices,semiconductors, precision mechanics, automotive, watchmaking, or machinery); experience in regulated environments is a plus
• 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.