- Design and implement a scalable and resilient IoT platform architecture to deliver multiple use cases, incorporating device management, data engineering, data-driven intelligence, and remote device control capabilities.

- Ensure the security and privacy of the IoT platform, adhering to industry best practices and regulatory standards.

- Integrate the IoT platform seamlessly with existing enterprise systems (e.g., ERP, CRM, SCM).

Hardware and Device Management :

- Develop and integrate robust device management capabilities, including provisioning, configuration, and monitoring

- Implement real-time device health monitoring and anomaly detection to proactively identify and address issues.

- Provide guidance and oversight of the on-ground hardware implementation, socializing learnings, best practices and templates.

Data Engineering and Analytics :

- Develop and implement robust data pipelines to ingest, process, and store IoT data.

- Ensure data quality and consistency through data cleaning, validation, and normalization.

- Implement real-time data processing and analytics to derive actionable insights.

- Create insightful visualizations and reports to communicate findings to stakeholders.

- Protect sensitive data through appropriate security measures and compliance with data privacy regulations.

Machine Learning and AI :

- Develop, train, and deploy machine learning models to extract valuable insights from IoT data.

- Implement edge AI solutions to process data locally on IoT devices, reducing latency and improving efficiency.

- Monitor model performance, retrain models as needed, and address performance degradation.

DevOps and Reusability :

- Implement robust CI/CD pipelines to automate the build, test, and deployment processes.

- Leverage infrastructure as code principles to automate infrastructure provisioning and management.

- Utilize containerization and orchestration technologies (e.g., Docker, Kubernetes) to deploy and manage the IoT platform.

- Design and develop modular components to promote reusability and scalability.

- Adhere to cloud-native development principles to build scalable and resilient applications.

Continuous Learning and Innovation :

- Stay up-to-date with the latest advancements in IoT technologies, cloud computing, and machine learning.

- Encourage experimentation and innovation to drive the development of industry first features and functionalities.

- Stay informed about industry trends and emerging technologies to identify opportunities for improvement.

- Foster a culture of collaboration and knowledge sharing within the team and across the organization.

Team Leadership and Mentorship :

- Lead and mentor a team of talented engineers to deliver high-quality solutions.

- Foster a culture of innovation, continuous learning, and experimentation.

- Collaborate effectively with cross-functional teams, including product management, engineering, and operations.

Qualifications :

- 11+ years of experience in designing, developing, and deploying IoT solutions.

- Strong understanding of IoT protocols (MQTT, CoAP, HTTP), device connectivity options (cellular, Wi-Fi, BLE, LoRaWAN), and cloud platforms (Azure IoT Hub, AWS IoT Core, Google Cloud IoT Core).

- Hands-on experience with data engineering, data pipelines, and data warehousing.

- Proficiency in programming languages like Node ,Python and use of AI enabled Development.

- Experience with machine learning and AI techniques, including model development, training, and deployment.

- Knowledge of cloud-native development principles and containerization technologies (Docker, Kubernetes).

- Experience with DevOps practices and CI/CD pipelines.

- Strong understanding of cybersecurity principles and best practices for IoT systems.

Key Technical Skills :

- IoT Protocols : MQTT, CoAP, HTTP, AMQP

- Cloud Platforms : Azure IoT Hub, Azure IOT Central

- Data Engineering : Stream Analytics, Power BI, Azure Databricks, Azure Data Lake etc

- Programming Languages : Python, Node , TypeScript

- Cloud-Native Development : Docker, Kubernetes, Serverless Computing , Event