What You'll Own

Device data ingestion

• Design high-throughput pipelines handling GPS, CAN bus, sensors, and accelerometer streams from thousands of concurrent devices.

Real-time processing

• Build and maintain streaming architectures on Kafka for event-driven alerts — harsh braking, geofence violations, engine fault codes.

Fleet visibility UI

• Develop ReactJS dashboards that surface live vehicle positions, trip replays, and sensor-derived KPIs to fleet operators.

Edge-to-cloud architecture

• Manage AWS IoT Core device registries, certificate provisioning, and shadow state for over-the-air configuration management.

Key Responsibilities

• Ingest and normalise high-frequency telemetry (GPS fixes, CAN signals, accelerometer data) from heterogeneous hardware vendors into a unified schema.
• Build low-latency Node.js microservices that decode proprietary device protocols (e.g. Teltonika, Calamp, Queclink) and route events to downstream consumers.
• Design time-series data models (InfluxDB, TimescaleDB, or DynamoDB) optimised for fleet analytics, driver scoring, idling hours, fuel anomalies.
• Implement geospatial features: geofencing, route matching, and stop detection using PostGIS or AWS Location Service.
• Build ReactJS interfaces for live map views, trip history replay, alert configuration, and sensor-level drill-down.
• Write Lambda functions and Step Functions workflows for asynchronous event processing, threshold breach notifications, and report generation.
• Write clean, well-tested code and participate in code reviews. Mentor junior engineers and champion data quality, observability, and reliability standards.

Required Experience

• 5+ years in software engineering, with at least 2 years working directly with IoT or telematics data (vehicle, asset, or device tracking).
• Strong Node.js and TypeScript skills; comfort with high-concurrency event-driven services.
• Hands-on experience with the Message Queuing system (RabbitMQ, Kafka, Amazon SQS).
• ReactJS and TypeScript for building data-dense operational UIs (maps, charts, data tables).
• AWS services: IoT Core, Lambda, RDS/Aurora, S3, CloudWatch.
• Time-series or geospatial databases: InfluxDB, TimescaleDB, PostGIS, or equivalent.
• Kafka for real-time event streaming: topic design, consumer groups, partition strategies, and delivery guarantees. Nice to Have
• Experience integrating with tachograph data, FMS standards, or J1939/J1708 truck protocols.
• Knowledge of cellular connectivity (2G/4G/LTE-M) and its impact on data loss, buffering, and reconnection strategies.
• Familiarity with mapping libraries: Mapbox GL JS, Leaflet, or deck.gl for large-scale vehicle data visualisation.
• Prior work in transport, logistics, or fleet management domains.
• Experience with Kafka: topic design, consumer groups, partition strategies, and at-least-once delivery guarantees.
• Understanding of DevOps practices: Docker, CI/CD pipelines, infrastructure-as-code