Manufacturing Process Analyst / Engineer (m/f/d) - S&C

Posted on November 11, 2026
Randstad Multilingual Recruitment
Risch
English
Temporary
Posted on November 11, 2026

About this role

For our client, a leading international life sciences and diagnostics company based in Rotkreuz, we are looking for a dedicated and qualified professional as a Manufacturing Science & Technology (MSAT) Engineer / Process Engineer (m/f/d) specializing in shop-floor engineering and data analytics.

 

As an MSAT Engineer (m/f/d), you will support the entire product lifecycle—from design transfer to sustainable product care for complex sensor and cartridge technologies. Working within an agile, cross-functional framework (Squads & Chapters), you will combine technical expertise, data-driven insights, and digital tools to solve complex challenges directly at the interface between development and production. You bring a pragmatic, hands-on mindset to the shop floor to effectively balance process robustness with strict quality standards.


 

General Information


 
  • Start Date: ASAP (latest 01/02/2027)

  • Duration of Employment: 1 year; with extension

  • Workplace: Rotkreuz (Canton of Zug)

  • Workload: 100%

  • Home Office: Not planned initially (focus on on-site onboarding); limited flexibility possible thereafter upon team alignment

  • Travel: No

     

Tasks & Responsibilities


 
  • Identify & Solve Gaps: Systematically analyze manufacturing processes to uncover limitations, root causes, and risks related to process robustness, control strategies, and equipment

  • Drive Improvements: Develop and implement actionable, practical 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 laboratory and manufacturing environments to support the scale-up of new production lines

  • Shop-Floor Collaboration: Partner closely with shift teams, operators, and maintenance technicians to align real-world machine challenges with robust engineering solutions

  • Compliance & Documentation: Create and maintain precise process documentation, change records, and work instructions in line with GxP standards


     

Qualifications & Requirements (Must-Haves)


 
  • Degree (Bachelor's or Master's) in Engineering (Mechanical, Mechatronics, Automation, Electrical, Micro/Precision Engineering), Physics, Materials Science, or equivalent practical experience

  • Practical industry experience (approx. 3–5 years) in complex automated production, robotics, high-precision assembly, dispensing/joining technologies, or delicate component handling

  • Background in regulated or precision-driven industries (e.g., medical devices, semiconductors, precision mechanics, automotive, watchmaking, or machinery)

  • Pragmatic shop-floor and quality mindset: strong on-site presence at the production line, practical problem-solving attitude toward deviations, and dedication to structured technical documentation in a GxP environment

  • Solid data and digital affinity: practical proficiency in at least one programming language (e.g., Python, R) to read and interpret data, or hands-on experience with modern digital tools

  • Strong interpersonal and collaboration skills: ability to connect effectively with operators on the floor and translate technical findings clearly for cross-functional teams

  • Agile mindset: experience with or strong enthusiasm for agile ways of working (e.g., Scrum, Kanban)

  • Professional fluency in both English and German (minimum B2 level in each)

  • Willingness to undergo Hepatitis vaccination (mandatory requirement for cleanroom and laboratory access)


     

Desirable Skills (Nice-to-Haves)


 
  • Familiarity with Continuous Improvement / Lean Six Sigma methods (e.g., SIPOC, value stream mapping, root-cause toolkits)

  • Experience in advanced statistical analysis, database queries (e.g., SQL, Snowflake), or digital manufacturing initiatives

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