Data Engineering for IoT
IoT platforms generate continuous telemetry from thousands of connected devices, demanding data infrastructure that handles high-throughput ingestion, real-time anomaly detection, and predictive analytics. I have built the data function from scratch for a 150+ enterprise client IoT platform — migrating legacy systems to AWS, building unified analytics dashboards, and integrating ML models for predictive maintenance. For IoT companies scaling beyond initial prototypes, I deliver the data architecture that turns sensor noise into operational intelligence.
IoT Data Challenges I Solve
High-throughput ingestion from thousands of heterogeneous device types
Legacy system migration without disrupting live device telemetry
Predictive maintenance models requiring clean, time-series data pipelines
Multi-tenant data isolation for enterprise client deployments
IoT Projects
AI-Powered IoT Operations Platform
Built the data function from scratch for a 150+ client IoT platform — from legacy migration to unified analytics on AWS
Technologies I Use for IoT
Other Industries
Building Data Infrastructure for IoT?
Let's discuss how modern data engineering can solve your iot data challenges.