Software Engineer - Telematics

Applied Intuition Applied Intuition · Robotics · Sunnyvale, CA · Vehicle OS

Software Engineer role focused on developing telematics platforms for connected devices, processing real-time telemetry data, and building scalable data processing pipelines using technologies like Kafka and Spark. The role involves backend development, cloud-native applications, and data storage/analytics solutions.

What you'd actually do

  1. Design and develop scalable robust telematics backend systems that process high-volume, real-time telemetry data streams from millions of connected devices using modern microservices architecture
  2. Architect and implement robust data processing pipelines using technologies like Apache Kafka, Apache Spark, and stream processing frameworks to handle telematics data ingestion, transformation, and analytics
  3. Develop cloud-based data storage and analytics solutions leveraging distributed databases, data warehouses, and time-series databases to support real-time monitoring and historical analysis
  4. Implement device-to-device (D2D) communication systems that enable direct data exchange between connected devices, reducing latency and improving network efficiency through peer-to-peer connectivity
  5. Collaborate with cross-functional teams including data scientists, DevOps engineers, product managers, and frontend developers to deliver comprehensive telematics solutions

Skills

Required

  • Go
  • C++
  • Python
  • AWS
  • Azure
  • Google Cloud Platform
  • Docker
  • Kubernetes
  • Apache Kafka
  • Apache Spark
  • MQTT
  • NATS
  • WebRTC
  • gRPC
  • SQL
  • NoSQL
  • RESTful services
  • microservices architecture
  • API security
  • CI/CD
  • infrastructure as code
  • monitoring
  • automated testing

Nice to have

  • real-time data processing
  • stream analytics
  • cloud security
  • IoT data protocols
  • telematics data sources
  • third-party aggregators
  • monitoring and observability tools
  • data visualization
  • business intelligence tools
  • event-driven architecture
  • serverless computing
  • agile development methodologies
  • automotive industry standards
  • fleet management
  • logistics applications

What the JD emphasized

  • 4+ years of experience in backend software development
  • strong proficiency in languages like Go, C++, Python
  • experience with cloud-native application development
  • Knowledge of data processing and streaming technologies including Apache Kafka, Apache Spark, MQTT, NATS, WebRTC, gRPC
  • experience building high-throughput data pipelines
  • Experience with database technologies including both SQL and NoSQL databases, data warehousing solutions, and time-series databases for handling large-scale telemetry data
  • Understanding of API design and development with experience in RESTful services, microservices architecture, and API security best practices
  • Knowledge of DevOps practices including CI/CD pipelines, infrastructure as code, monitoring, and automated testing frameworks
  • Strong problem-solving skills and ability to work in fast-paced cloud development environments with mission-critical, high-availability systems