Associate Principal Engineer - IoT Platform

Description

Key Responsibilities :

• IoT Platform Architecture and Design
• 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
• DevOps : CI/CD pipelines, Infrastructure as Code (IaC)