Process Engineer

Process Engineer

NanoAvionics

Vilnius, Lithuania

We are seeking an experienced Process Engineer to drive industrialization, process optimization, and continuous improvement across whole satellite manufacturing operations. The role focuses on the full product lifecycle – from component design requirements to production, assembly, integration and testing.

As Process Engineer, you will:

• Evaluate bottlenecks and conduct analyses to produce data driven industrialization business cases;
• Introduce lean manufacturing, 5S, and similar continuous improvement practices;
• Develop, optimize, and document assembly, integration, and testing processes for satellite subsystem production;
• Act as a technical stakeholder and lead for industrialization initiatives for KNA‘s products and ensuring repeatability, efficiency, and quality;
• Collaborate with design, quality, and production teams to ensure manufacturability, testability, and supply chain efficiency;
• Work with external equipment/tool or material suppliers in the selection, design, and development of new (or upgrades to existing) equipment, tools and materials;
• Analyze production and test data to identify process deviations and implement corrective actions.

We expect you to have:

• Have a technical degree in Industrial Engineering, Mechanical Engineering, Electronics, or related field;
• 3+ years of process or manufacturing engineering experience in high-reliability or complex production environments;
• Knowledgeable in manufacturing execution systems such as lean, 6sigma, statistical process control (SPC), and FMEA methodologies;
• Strong analytical and problem-solving abilities with competence in data-driven decision-making;
• Excellent communication skills and ability to work cross-functionally with production, testing, design, and supply chain teams.

Nice to have:

• Hands-on experience in PCBA manufacturing, assembly, and test process definition;
• Familiarity with environmental (vibration, thermal, EMC) and functional test methodologies;
• Prior experience in process development, production management, automation;
• Experience with ERP tools;
• Working with data models, having experience in handling complex information tidy, discrete event simulation.