Work Location: North
Salary: 6,500 - 8,000
- Provide technical leadership in a high-volume consumables manufacturing environment, supporting the implementation and optimization of smart manufacturing systems.
- Troubleshoot, maintain, and optimize manufacturing equipment involving optical, mechanical, electrical, and fluidics systems.
- Drive improvements in equipment uptime, reliability, and overall manufacturing performance through continuous improvement initiatives.
- Lead and support New Product Introduction (NPI) activities, ensuring successful equipment readiness and process implementation.
- Apply engineering principles and systematic problem-solving techniques to resolve complex manufacturing and equipment-related issues.
- Identify and implement equipment performance enhancements to improve productivity, quality, and operational efficiency.
- Analyze equipment performance data to identify trends, determine root causes, and recommend data-driven solutions.
- Support the adoption of data analytics tools and methodologies to improve manufacturing decision-making and equipment reliability.
- Develop, train, and mentor Technicians and Engineers to enhance technical capabilities and ensure compliance with performance standards.
- Provide leadership, guidance, and day-to-day supervision to the assigned engineering team.
- Collaborate with cross-functional teams, including Manufacturing, Quality, Process Engineering, and Operations, to achieve production and business objectives.
- Ensure compliance with safety, quality, and regulatory requirements while promoting engineering best practices and continuous improvement.
Requirements:
- Diploma or higher qualification in Electrical, Electronics, Mechanical, or Mechatronics Engineering, with at least 6 years of experience in a manufacturing environment.
- Exposure to data analytics is an advantage, including the ability to analyze equipment performance, identify trends, and support data-driven decision-making. Familiarity with digital and analytics tools such as Statistical Process Control (SPC), Python, Power BI, Tableau or Power Automate for data analysis, visualization, reporting, and workflow automation.
EA Registration no: R1215243
