Experience Required :

- 10 - 12 years of overall experience in software/industrial systems, including at least 2 3 years in an architectural or technical leadership role.

- Demonstrated experience in designing and deploying IIoT or large-scale industrial data solutions.

- Prior exposure to manufacturing, Industry 4.0, or industrial automation use cases is highly desirable.

Key Responsibilities :

- Design and develop front-end dashboards and analytics modules using React. Define and maintain end-to-end IIoT architecture spanning edge devices, gateways, cloud platforms, and applications.

- Design high-throughput, low-latency data pipelines capable of handling large-scale machine and sensor data for ingestion, storage, and analytics.

- Select and recommend technology stacks, protocols, databases, cloud services, and middleware aligned with scalability and performance goals.

- Ensure system scalability, fault tolerance, high availability, and enterprise-grade cybersecurity across deployments.

- Collaborate closely with Machine Integrators and Software Engineers to translate architecture into seamless implementations.

- Anticipate future scaling needs and build reusable, modular, and extensible system components.

- Evaluate system bottlenecks, latency issues, and performance trade-offs, and propose optimizations to balance cost, speed, and reliability.

- Provide technical leadership, define best practices, and maintain clear architectural documentation and standards.

- Drive innovation and technology adoption for advanced IIoT use cases such as predictive maintenance, real-time analytics, and digital twins.

Required Skills & Qualifications :

- 8 - 12 years of experience in software engineering, with at least 35 years in a solution/system architect role.

- Proven expertise in designing large-scale IIoT or industrial data platforms with high-volume, real-time data flows.

- Strong understanding of industrial communication protocols (OPC-UA, MQTT, Modbus, Profinet, Ethernet/IP).

- Hands-on experience with system design across edge, middleware, and cloud platforms.

- Proficiency in databases (SQL, NoSQL, Time-series DBs) for large-scale data storage and analytics.

- Solid grounding in cloud-native solutions (Azure IoT, AWS IoT, GCP) and distributed systems.

- Strong knowledge of DevOps practices (CI/CD pipelines, Docker, Kubernetes).

- Ability to design for scalability, high availability, fault tolerance, and cybersecurity in IIoT ecosystems.

- Strong analytical, problem-solving, and communication skills with the ability to lead cross-functional teams.

Good to Have (Optional) Skills :

- Experience with manufacturing analytics, predictive maintenance, or digital twin solutions.

- Exposure to AI/ML models applied to industrial and sensor data.

- Familiarity with streaming and messaging platforms (Kafka, RabbitMQ, Azure Event Hub).

- Knowledge of enterprise OT/IT security standards and compliance frameworks.

- Prior experience in performance tuning, cost optimization, and architectural governance.

- Scrum fundamentals and familiarity with Agile delivery tools (Jira, Azure DevOps).