Internet of Things Consultant

About Clinet :

A specific global digital engineering and technology solutions company, headquartered in Munich, Germany, operates with approximately 18,000 employees across 39 countries. This organization provides a full spectrum of services including digital product engineering, AI and data analytics, cloud services, and enterprise consulting for clients such as a major German airline group, a global logistics and shipping firm, and an automobile manufacturer specializing in premium vehicles. The company is publicly traded on the Frankfurt Stock Exchange and recorded approximately $1 billion in annual revenues in FY23, demonstrating a significant presence in the global technology services market.

Our client is known for its distinctive flat hierarchy, agile delivery model, and entrepreneurial mindset. Its operational philosophy is guided by core values that emphasize a client-centric, intelligent, and non-hierarchical approach. The company focuses on empowering small, autonomous teams to be responsive and adaptable to complex business challenges, fostering a flexible and inclusive work culture. It is committed to leveraging advanced technologies like AI and cloud services to help its diverse client base become more digitally mature and human-centric organizations.

Job Title : IOT Architect

Location : Gurugram

Experience : 11+ years

Employment Type : Contract to hire

Notice Period : Immediate joiners

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.