Live opening · Posted 27 days ago
The key details from the original listing.
Live timing from JobBeeper.
Description supplied by the original job listing.
Responsibilities:
Lead the design and delivery of end-to-end industrial IoT architecture spanning edge to cloud, enabling real-time data ingestion, time-series analytics, and cloud-scale AI/analytics for manufacturing and industrial operations.
Drive platform strategy, standardisation, and scalability of IIoT solutions aligned with enterprise data and AI platforms.
Define and implement edge-cloud IIoT architecture (edge devices, streaming, cloud analytics, AI).
Design real-time data pipelines for high-frequency industrial/time-series data.
Architect integration of OT systems (PLC, SCADA, MES) with cloud data lakehouse platforms.
Lead cloud analytics strategy (streaming, batch, AI/ML on industrial data).
Establish IIoT platform standards (data models, ingestion patterns, governance, security).
Design observability solutions using Grafana + time-series platforms.
Ensure scalability, resilience, and security of IoT ecosystems.
Partner with data, AI, and business teams to enable use cases: Predictive maintenance, asset performance monitoring, quality analytics, energy optimisation.
Success Metrics:
Scalable, standardised edge-to-cloud IIoT platform.
Reliable real-time ingestion and processing of industrial data.
Enterprise adoption of cloud analytics on IIoT data.
Measurable impact on uptime, efficiency, and operational visibility.
Requirements:
Bachelor's/Master's in engineering, computer science, or a related field.
8-12+ years in IoT/IIoT, data platforms, or industrial automation.
Proven experience designing real-time, cloud-scale IIoT architectures.
Required Skills: Architecture and Platforms.
Edge-Cloud Architecture: gateways, edge computing, cloud ingestion, and analytics layers.
GCP Analytics Stack: Pub/Sub, Dataflow, BigQuery, Bigtable, Vertex AI.
Time-Series Platforms: InfluxDB, TimescaleDB, Bigtable.
Streaming and Real-Time Analytics: Kafka / Pub/Sub, event-driven architectures.
Visualisation: Grafana.
Industrial and Integration:
OT systems: PLC, SCADA, MES.
Protocols: OPC-UA, MQTT, Modbus.
Experience integrating factory systems with enterprise data platforms.
Data and AI:
Real-time analytics, data pipelines, and lakehouse architectures.
ML/AI use cases on industrial data (predictive maintenance, anomaly detection).
Security and Networking:
IoT security (device identity, encryption, zero-trust principles).
Industrial network architectures.
Experience
9-13 yrs
Recently tracked roles with full details and direct application links.