Your role
oT Edge & Data Center Integration
- Design and deploy Azure IoT Edge workloads running on data center gateways/servers to ingest telemetry from: - BMS/BAS systems
- Power systems (UPS, PDUs, ATS, Generators)
- Cooling and mechanical systems
- Environmental sensors (temperature, humidity, airflow, water leak)
- IT infrastructure (SNMP, Modbus, BACnet, OPC-UA)
- Build MQTT-based ingestion pipelines to securely stream telemetry from local DCIM collectors into the Azure cloud.
- Implement local processing logic for buffering, aggregation, transformation, and on-premise failover.
Cloud Data Pipeline Engineering
- Develop end‑to‑end data flows using Azure IoT Hub, Event Hub, Stream Analytics, Azure Functions, Data Explorer, and Storage.
- Build scalable and secure APIs and microservices to expose telemetry for customers, partners, and internal services.
- Implement real-time alarming and event processing in the cloud using serverless compute.
- Integrate telemetry into analytics platforms to support: - Predictive maintenance
- Capacity forecasting
- Energy efficiency AI models
- SLA/uptime reporting
Platform Reliability & Operations
- Implement robust monitoring, diagnostics, and observability using Log Analytics, Azure Monitor, and Application Insights.
- Troubleshoot connectivity, protocol translation, cloud ingestion, and Edge deployment issues.
- Ensure configuration management and version control of IoT Edge modules.
Security & Compliance
- Implement strong end‑to‑end security across: - Device identity and certificates
- Encrypted MQTT communication
- Secure onboarding with DPS
- Azure RBAC and Key Vault-based secrets management
- Ensure solutions meet data center security policies and customer data governance requirements.
Collaboration & Documentation
- Partner with DC Operations, Facilities, Product Management, Data Science, and Customer Engineering teams.
- Document architecture, deployment processes, and support handover materials.
- Contribute to design standards and best practices for DCIM modernization.
What you’ll need
Technical Skills
- Strong hands-on experience with: - Azure IoT Hub, IoT Edge, IoT Hub Device Provisioning Service
- MQTT protocol and edge-to-cloud messaging
- Azure Functions, Event Hub, Stream Analytics, Azure Data Explorer (Kusto)
- Container development (Docker) and Edge module creation
- C#, Python, Node.js, or Go for backend and edge services
- Familiarity with data center protocols and devices: - Modbus RTU/TCP, BACnet/IP, SNMP, OPC-UA
- Environmental sensors and telemetry networks
- Experience with CI/CD pipelines (Azure DevOps or GitHub Actions)
- Knowledge of IaC (Bicep, ARM, Terraform)
Experience
- Prior experience in data center infrastructure, building systems, or industrial IoT environments.
- Designing event-driven cloud architectures for real-time monitoring.
- Building resilient telemetry ingestion systems.
- Working with operational technology (OT) in secure environments.
Responsibilities
oT Edge & Data Center Integration
- Design and deploy Azure IoT Edge workloads running on data center gateways/servers to ingest telemetry from: - BMS/BAS systems
- Power systems (UPS, PDUs, ATS, Generators)
- Cooling and mechanical systems
- Environmental sensors (temperature, humidity, airflow, water leak)
- IT infrastructure (SNMP, Modbus, BACnet, OPC-UA)
- Build MQTT-based ingestion pipelines to securely stream telemetry from local DCIM collectors into the Azure cloud.
- Implement local processing logic for buffering, aggregation, transformation, and on-premise failover.
Cloud Data Pipeline Engineering
- Develop end‑to‑end data flows using Azure IoT Hub, Event Hub, Stream Analytics, Azure Functions, Data Explorer, and Storage.
- Build scalable and secure APIs and microservices to expose telemetry for customers, partners, and internal services.
- Implement real-time alarming and event processing in the cloud using serverless compute.
- Integrate telemetry into analytics platforms to support: - Predictive maintenance
- Capacity forecasting
- Energy efficiency AI models
- SLA/uptime reporting
Platform Reliability & Operations
- Implement robust monitoring, diagnostics, and observability using Log Analytics, Azure Monitor, and Application Insights.
- Troubleshoot connectivity, protocol translation, cloud ingestion, and Edge deployment issues.
- Ensure configuration management and version control of IoT Edge modules.
Security & Compliance
- Implement strong end‑to‑end security across: - Device identity and certificates
- Encrypted MQTT communication
- Secure onboarding with DPS
- Azure RBAC and Key Vault-based secrets management
- Ensure solutions meet data center security policies and customer data governance requirements.
Collaboration & Documentation
- Partner with DC Operations, Facilities, Product Management, Data Science, and Customer Engineering teams.
- Document architecture, deployment processes, and support handover materials.
- Contribute to design standards and best practices for DCIM modernization.
Qualifications
Technical Skills
- Strong hands-on experience with: - Azure IoT Hub, IoT Edge, IoT Hub Device Provisioning Service
- MQTT protocol and edge-to-cloud messaging
- Azure Functions, Event Hub, Stream Analytics, Azure Data Explorer (Kusto)
- Container development (Docker) and Edge module creation
- C#, Python, Node.js, or Go for backend and edge services
- Familiarity with data center protocols and devices: - Modbus RTU/TCP, BACnet/IP, SNMP, OPC-UA
- Environmental sensors and telemetry networks
- Experience with CI/CD pipelines (Azure DevOps or GitHub Actions)
- Knowledge of IaC (Bicep, ARM, Terraform)
Experience
- Prior experience in data center infrastructure, building systems, or industrial IoT environments.
- Designing event-driven cloud architectures for real-time monitoring.
- Building resilient telemetry ingestion systems.
- Working with operational technology (OT) in secure environments.
Preferred Qualifications
- Azure certifications: AZ‑204, AZ‑220, AZ‑305 or equivalent.
- Experience with: - Data center DCIM systems
- Power and cooling system integration
- High-availability IoT solutions
- Digital twins (Azure Digital Twins or equivalent)
- AI/ML pipelines for anomaly detection and forecasting
- Familiarity with edge networking, firewalls, proxies, VPNs, and OT/IT segmentation.