Total 2 Senior Executive data entry job vacancies in Batu Kawan

Act as the key local expert and lead user for planning-relevant master data, ensuring high consistency, quality and reliability of data used in Blue Yonder to support holistic planning of the semiconductor production network.

Serve as a critical interface between business, specialty departments, IT, and external IT service providers, driving further development, stabilization and continuous improvement of master data and planning IT solutions.

Utilize cost advantages of LCL.

• Drive end‑to‑end planning master-data quality and governance, ensuring reliable, usable data across business functions
• Act as technical lead for analytics and data solutions (Power BI, SQL Oracle/MSSQL, KNIME, databases, web/UI tools)
• Responsible for maintenance and enhancement of master data applications and UIs (e.g. Tivity) aligned with business needs
• Drive dashboards and advanced analytics to enable planning excellence, transparency, and self‑service insights
• Lead root cause analysis of complex data issues, implementing sustainable, preventive solutions
• Define, monitor and improve data governance frameworks, validation rules, workflows, KPIs and operating models
• Identify data quality trends and drive automation, structural improvements and scalability
• Ensure data solutions effectively support planning processes (demand planning, logistics interfaces, master data flows)
• Manage global and local stakeholder expectations, priorities and dependencies with clear, business‑oriented communication
• Motivate and develop the team by setting technical standards, best practices and ways of working
• Foster a culture of ownership, continuous improvement, analytical thinking and knowledge sharing
• Lead and contribute to PJM1‑SO projects, driving innovation, efficiency and advanced analytics adoption

ESSENTIAL DUTIES AND RESPONSIBILITIES: 

• Perform data mining and analytics for Quality Assurance (QA) in semiconductor Assembly & Testing processes
• Understand QA business workflows (e.g., SPC, 8D, defect management) and translate business needs into scalable data solutions
• Design and develop end-to-end data pipelines, including data ingestion, transformation, modeling, and visualization
• Develop analytical methods such as anomaly detection, trend analysis, and predictive modeling to enhance quality control
• Drive the transformation of quality management from manual processes to automated and intelligent systems
• Develop dashboards, reports, and automated QA-related business applications
• Collaborate with IT, data teams, and business stakeholders to integrate data platforms with operational systems
• Explore and implement AI/GenAI use cases in quality engineering, such as intelligent insights and automated reporting