Job
Description
Role & responsibilities Design and develop SCADA/HMI applications for monitoring, control, visualization, and data logging using platforms like Wonderware, Ignition, WinCC, or Citect Interface SCADA with PLCs (Siemens, Allen-Bradley, etc.) and industrial protocols (OPC UA, Modbus, Ethernet/IP) Develop a real-time condition monitoring system using sensors (vibration, temperature, current, etc.) integrated with DAQs or embedded platforms Implement predictive analytics and machine learning models to detect faults, estimate health indices, and predict failures (RUL) Design and deploy self-healing logic that initiates corrective actions (via PLC or edge devices) to minimize downtime Build dashboards for equipment diagnostics, historical trends, and alerts using visualization tools (Grafana, Power BI, Ignition Perspective, etc.) Integrate SCADA, CMS, and analytics into a seamless user interface Coordinate with cross-functional teams (mechanical, instrumentation, software) to understand failure modes and operational needs. Conduct field validation, testing, and commissioning of systems on live equipment. Ensure system security, uptime, scalability, and compliance with industrial standards. Required Skills & Qualifications: Bachelors or Master’s in Electrical, Electronics, Mechatronics, Instrumentation, or Computer Engineering 5+ years’ experience in SCADA development, control systems integration, or industrial automation Solid understanding of sensor data acquisition , signal processing, and industrial instrumentation Hands-on with PLC programming and control logic (Siemens, Allen-Bradley, etc.) Strong knowledge of Python, MATLAB , or equivalent for data analytics and AI model development Experience with machine learning libraries (TensorFlow, PyTorch, scikit-learn) Familiarity with edge computing platforms (Jetson Nano, etc.) and IIoT integration (AWS IoT, Azure IoT Edge) Proficient in SQL/time-series databases (InfluxDB, TimescaleDB) and visualization platforms Knowledge of industrial failure modes and predictive maintenance methodologies Excellent troubleshooting, problem-solving, and documentation skills
