The Data Engineer role supports data-driven manufacturing operations in Mueang, Chonburi. The position focuses on developing reliable data infrastructure, real-time monitoring platforms, analytical models, and operational dashboards to identify production opportunities, improve machine performance, and support process optimisation.
Responsibilities
Design and maintain robust Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) pipelines to ingest data from programmable logic controllers, computer numerical control machines, Internet of Things sensors, Manufacturing Execution Systems, Enterprise Resource Planning systems, and Computerised Maintenance Management Systems
Design and manage data warehouse and lakehouse schemas, ensuring high data quality and effective metadata management
Develop streaming platforms for real-time monitoring of machine utilisation, downtime alerts, and shop-floor metrics
Build and deploy anomaly detection and Remaining Useful Life (RUL) estimation models using time-series analysis, including ARIMA, LSTM, and Prophet
Use data to identify production bottlenecks, optimise setup and changeover times, and improve overall throughput
Analyse repair histories and machine logs to identify failure patterns and extend Mean Time Between Failures (MTBF)
Create high-impact dashboards using Power BI or Tableau to integrate data-driven insights into daily operations
Conduct pre- and post-implementation comparisons, A/B testing, and Design of Experiments (DOE) to measure the actual return on investment of process improvements
Requirements
At least 3 years of experience in data engineering, data science, or manufacturing analytics
Proficiency in Python, including Pandas, NumPy, Scikit-learn, and PyTorch or TensorFlow
Strong proficiency in SQL for complex data manipulation
Practical knowledge of manufacturing data, including shop-floor measurements, Overall Equipment Effectiveness (OEE), Mean Time to Repair (MTTR), Mean Time Between Failures (MTBF), and maintenance logs
Ability to communicate technical insights clearly to non-technical stakeholders
Hands-on experience with Microsoft Azure, including IoT Hub, Databricks, or Synapse, or experience with Amazon Web Services or Google Cloud Platform
Experience in reliability engineering, including Weibull analysis, or analysing logs from computer numerical control machine tools such as FANUC or Mitsubishi
Familiarity with production-grade quality assurance, model monitoring, and security access control
About the company
A company in the precision manufacturing industry with operations in Thailand. The organisation manufactures precision-machined metal components for customers across the automotive, motorcycle, and air-conditioning industries.