Digital Service lead Engineer
By
Kartik
6h agoen
Source
Saur EnergyDigital Service lead Engineersaurenergy.comHow you’ll make an impact: Configure and deploy IoT edge devices/gateways for industrial applications. Implement communication using protocols such as Modbus, MQTT, OPC UA, IEC 60870-5-104, IEC 60870-5-101. Integrate field devices (IEDs, sensors, PLCs) with IoT platforms and cloud systems. Perform protocol mapping, data acquisition, and signal validation. Design and understand southbound (device-level) and northbound (cloud/enterprise) communication flows. Configure and troubleshoot gateway communication, network connectivity, and data flow issues. Work on edge-to-cloud integration, including MQTT broker configuration and OPC UA mapping. Support commissioning, testing, and validation of IoT deployments. Maintain documentation of configurations, architecture, and troubleshooting steps. Collaborate with IT/OT teams for secure and scalable solution deployment. Perform troubleshooting and root cause analysis (RCA) for issues, and propose corrective and preventive actions to avoid recurrence Contribute to enhancing system performance and reliability through continuous analysis and technical recommendations. Your background: Have B.E in Electrical & Electronics Engineering with a minimum work experience of 5+ years in configuring RTU’s, SCADA, IOT devices Self-starter caliber who could own tasks through to completion. Excellent written and verbal communication skills Preferred Qualifications Good knowledge of MS Office tools You must have Knowledge & Skills in: Hands-on experience in IoT device configuration and communication setup configuring IoT edge devices, RTU using industrial protocols (Modbus, MQTT, OPC UA, IEC 104/101) Exposure to substation/industrial automation systems (SCADA, IEDs) Good knowledge of TCP/IP networking, ports, firewalls, Edge device configuration and troubleshooting, Data mapping (signal-to-topic/schema mapping) Ability to interpret and work with system architecture diagrams and deployment models
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