Deskripsi pekerjaan

Quality Engineer - Digital Responsible Partnered with IT and Automation to lead the deployment of the IoT MES LIME system, unified data from IOT MES LIMS and automation systems, performed multi level comparative analysis on inspection and process data, and built an integrated cross level database to support process improvement and decision making.

Tanggung jawab: Collaborate with IT, Automation, and MES/LIMS teams to lead the construction and rollout of quality and process modules of IoT, MES, and LIMS systems, taking charge of requirements gathering, blueprint design, system implementation, UAT validation, and da; Coordinate with IT, Automation, and MES/LIMS teams on daily system operations and maintenance, user technical support, and rapid fault response; Extract, clean, and integrate data from multiple source systems (IoT, MES, LIMS, etc.) to build a unified digital database of core business processes; Design and optimize data warehouse models and data architecture, establish data governance policies (including data standards, metadata management, and master data management), and ensure data consistency and availability; Establish a data quality monitoring indicator system, continuously track data reliability, identify and resolve quality issues at the source, maintain robust data pipelines and models, and ensure analytical accuracy; Utilize data analysis and visualization tools to discover, model, and analyze end-to-end business processes, identifying bottlenecks, deviations, and improvement opportunities; Generate clear, actionable insights and recommendations for stakeholders, translate complex data findings into concrete process improvement measures, and monitor post-implementation performance to ensure sustained improvement; Provide training to regional quality supervisors and QMs on the use of LIMS, MES, and IoT systems to enhance team operational capabilities; Lead ongoing optimization of system issues, manage the review of new project requirements and development coordination, and act as a bridge between Data/IT and Automation teams to ensure solutions address core pain points; Participate in the long-term strategic planning for process and quality analytics functions, including tool evaluation, methodology standardization, and team capability building; Efficiently complete other tasks assigned by the supervisor and ensure timely closure of all work items; · Candidates must possess at least a Bachelor’s degree in Quality, Science, Information Technology, Industrial Engineering, Mechanical Engineering, Chemical Engineering, or a related field; · Experience in manufacturing processes, desirable from aseptic or flexible packaging; · Experience in data analysis of manufacturing operations; · Experience with process mining tools (e.g., Celonis, UiPath Process Mining, Minitab) is a plus; · Proficiency in data visualization tools to create dashboards; · Knowledge of programming for advanced analytics, predictive modeling, and automating data pipelines; · Ability to understand and create standard process diagrams to connect data insights to concrete process steps; · Good knowledge of Continuous Improvement tools such as lean manufacturing, Kaizen, 6 sigma; · Good cross functional communication and teamwork skills; · Good office computer skills; · Working English proficiency to read technical manuals, equipment specifications, and engineering drawings / documents in English; communicate with overseas equipment suppliers / vendors for installation, maintenance, or troubleshooting support; and prep; · Meets minimum health requirements as evidenced by Pre-Employment Medical Check-Up (MCU) result of Fit to Work or Fit with Notes, as confirmed by the EHS team in accordance with the Company’s Health Requirements Matrix nad applicable occupational health; [Our company upholds the principles of equal employment opportunity and non-discrimination. We are committed to fostering a diverse and inclusive workforce without regard to race, religion, color, national origin, gender, sexual orientation, age, marital.

Tanggung jawab

Collaborate with IT, Automation, and MES/LIMS teams to lead the construction and rollout of quality and process modules of IoT, MES, and LIMS systems, taking charge of requirements gathering, blueprint design, system implementation, UAT validation, and da
Coordinate with IT, Automation, and MES/LIMS teams on daily system operations and maintenance, user technical support, and rapid fault response
Extract, clean, and integrate data from multiple source systems (IoT, MES, LIMS, etc.) to build a unified digital database of core business processes
Design and optimize data warehouse models and data architecture, establish data governance policies (including data standards, metadata management, and master data management), and ensure data consistency and availability
Establish a data quality monitoring indicator system, continuously track data reliability, identify and resolve quality issues at the source, maintain robust data pipelines and models, and ensure analytical accuracy
Utilize data analysis and visualization tools to discover, model, and analyze end-to-end business processes, identifying bottlenecks, deviations, and improvement opportunities
Generate clear, actionable insights and recommendations for stakeholders, translate complex data findings into concrete process improvement measures, and monitor post-implementation performance to ensure sustained improvement
Provide training to regional quality supervisors and QMs on the use of LIMS, MES, and IoT systems to enhance team operational capabilities
Lead ongoing optimization of system issues, manage the review of new project requirements and development coordination, and act as a bridge between Data/IT and Automation teams to ensure solutions address core pain points
Participate in the long-term strategic planning for process and quality analytics functions, including tool evaluation, methodology standardization, and team capability building
Efficiently complete other tasks assigned by the supervisor and ensure timely closure of all work items
· Candidates must possess at least a Bachelor’s degree in Quality, Science, Information Technology, Industrial Engineering, Mechanical Engineering, Chemical Engineering, or a related field
· Experience in manufacturing processes, desirable from aseptic or flexible packaging
· Experience in data analysis of manufacturing operations
· Experience with process mining tools (e.g., Celonis, UiPath Process Mining, Minitab) is a plus
· Proficiency in data visualization tools to create dashboards
· Knowledge of programming for advanced analytics, predictive modeling, and automating data pipelines
· Ability to understand and create standard process diagrams to connect data insights to concrete process steps
· Good knowledge of Continuous Improvement tools such as lean manufacturing, Kaizen, 6 sigma
· Good cross functional communication and teamwork skills
· Good office computer skills
· Working English proficiency to read technical manuals, equipment specifications, and engineering drawings / documents in English; communicate with overseas equipment suppliers / vendors for installation, maintenance, or troubleshooting support; and prep
· Meets minimum health requirements as evidenced by Pre-Employment Medical Check-Up (MCU) result of Fit to Work or Fit with Notes, as confirmed by the EHS team in accordance with the Company’s Health Requirements Matrix nad applicable occupational health
[Our company upholds the principles of equal employment opportunity and non-discrimination. We are committed to fostering a diverse and inclusive workforce without regard to race, religion, color, national origin, gender, sexual orientation, age, marital

Quality Engineer - Digital

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