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).(ref : hirist.tech)