Key Responsibilities
- Lead the solution architecture for Digital Twin rollouts, including high-level and detailed design of twin models, data architecture, integration patterns, and deployment strategy.
- Define end-to-end architecture covering:
- Digital Twin model hierarchy and entity relationships
- Real-time data ingestion and synchronization from IoT, SCADA, historians, and edge devices
- State management, event processing, and simulation engines
- Integration with enterprise systems (ERP, MES, PLM, EAM)
- Analytics, and visualization layers
- Select and design the optimal technology stack for scalable digital twin deployments, including in-memory computing platforms (e.g., ScaleTwin/ScaleOut), cloud services (AWS, Azure), streaming platforms (Kafka, MQTT), and containerization (Kubernetes).
- Create architecture blueprints, diagrams, and documentation (including logical, physical, and deployment views) to guide implementation teams.
- Conduct architecture reviews, risk assessments, and performance/scalability evaluations for large-scale twin deployments handling millions of entities and high-velocity data.
- Collaborate with Configuration Leads, Consultants, Data Engineers, and Client Stakeholders to ensure the solution is configurable, maintainable, and aligned with business requirements.
- Define standards, best practices, and reusable reference architectures for future Digital Twin rollouts.
- Provide technical leadership during pilot phases, full-scale rollout, go-live, and hyper-care periods.
- Mentor configuration teams on digital twin architecture principles.
Required Qualifications & Experience
- 10+ years of overall IT/solution architecture experience, with at least 4–6 years in Digital Twin, IIoT, IoT platforms, or real-time simulation solutions.
- Proven track record in successfully architecting and rolling out large-scale Digital Twin solutions for manufacturing, logistics, energy, or asset-intensive industries.
- Strong expertise in:
- Digital Twin platforms and frameworks (ScaleTwin, ScaleOut Digital Twins, Azure Digital Twins, NVIDIA Omniverse, or equivalent)
- Real-time data architectures (Kafka, MQTT, OPC UA, Spark Streaming)
- Cloud platforms (AWS IoT, Azure IoT Hub, Google Cloud)
- In-memory computing, complex event processing, and stateful applications
- Microservices, containerization (Docker, Kubernetes), and DevOps practices
- Bachelor's or Master's degree in Computer Science, Electrical/Mechanical/Industrial Engineering, or related field.
