Full-stack Senior Software Engineer — AI/IoT

Embedded IoT / iES

Distributed analytics pipeline processing 15,000+ records/minute from 5,000+ IoT devices.

A distributed Python + Node.js microservices pipeline for IoT stream analytics, ingesting telemetry from thousands of devices via Apache Kafka and Flink with Redis caching and ML anomaly detection.

01. The Challenge

Ingest and analyse high-velocity telemetry from thousands of devices in real time without overwhelming the database.

02. The Solution

Deployed distributed Python + Node.js microservices over Kafka + Flink, added Redis caching to cut DB load, and implemented ML anomaly-detection agents for predictive maintenance.

03. The Outcome

Processed 15,000+ records/minute from 5,000+ connected devices, cut downtime 50% and reduced DB load 75% across 25M+ records with sub-second queries.

15K rec/min

Throughput

5,000+

Devices

-50%

Downtime

-75%

DB load