Data Analytics Engineer

ESSENTIAL DUTIES AND RESPONSIBILITIES: 

• Identify, analyse, and resolve manufacturing process and quality-related issues through data-driven approaches.
• Develop, implement, and maintain Fault Detection (FD), Predictive Analytics, and Run-to-Run (R2R) control models to improve process stability, yield, and equipment performance.
• Lead and participate in continuous improvement initiatives focused on yield enhancement, cycle time reduction, productivity improvement, and manufacturing cost optimisation.
• Perform exploratory data analysis (EDA) across multiple manufacturing data sources to uncover patterns, root causes, and improvement opportunities.
• Design, develop, and deploy Advanced Process Control (APC) and Machine Learning models to address manufacturing quality and process challenges.
• Collaborate with cross-functional teams including Process Engineering, Equipment Engineering, Quality, IT, and Operations to implement and sustain SPC, FDC, RMS, APC, and ML-based solutions.
• Validate data quality, ensure data completeness, and monitor model performance to maintain solution effectiveness and reliability.
• Develop model monitoring and retraining strategies to ensure long-term predictive accuracy and business value.
• Document analytical methodologies, model assumptions, results, and lessons learned in knowledge management systems, ensuring documentation remains current and accessible.
• Extract, transform, and analyse data using SQL, NoSQL, Python, Spark, and other analytics tools from manufacturing databases, historians, MES, equipment logs, and cloud platforms.
• Communicate technical findings and recommendations effectively to stakeholders through dashboards, reports, and presentations.
• Stay current with emerging technologies in Data Analytics, Artificial Intelligence (AI), Machine Learning (ML), Industrial IoT, and Smart Manufacturing to drive innovation and operational excellence.