Onstar Vehicle Data System Engineer

General Motors

Warren, United States
Hybrid
End-to-end operational kpi
Data collection from gm vehicles
Operational metrics/insights
The OnStar Vehicle Data System Engineer is responsible for establishing and laying the grounds for End-to-End operational KPI of Products/platforms related services based on the technology of data collection from GM vehicles, and lead in the space of Operational metrics/insights

Job Summary

  • The OnStar Vehicle Data System Engineer is responsible for establishing and laying the grounds for End-to-End operational KPI of Products/platforms related services based on the technology of data collection from GM vehicles, and lead in the space of Operational metrics/insights.
  • This role will be part of the Connected Ops vehicle operations team that supports vehicle data-based services i.e. (OnStar services delivered using cellular connection CDMA/LTE such as mobile apps OnStar Vehicle Diagnostics, Vehicle Health Alerts, Theft Alert Notification, driving insights, Intelligent Virtual Assistant (IVA),HSVT (High Speed Vehicle Telemetry) mobile app’s location sharing, digital operations, chat bots, virtual advising, etc.
  • The individual will work as a member of a multi-disciplinary and cross organizational team of various experience levels that will be driving solutions by designing, developing, and deploying analytic models to measure performances supporting critical business areas and build automated data quality monitoring frameworks to ensure vehicle data meets high integrity standards.

Matching Summary

The OnStar Vehicle Data System Engineer is responsible for establishing and laying the grounds for End-to-End operational KPI of Products/platforms related services based on the technology of data collection from GM vehicles, and lead in the space of Operational metrics/insights.

Skills & Requirements

Must-have

  • End-to-End operational KPI
  • Data collection from GM vehicles
  • Operational metrics/insights
  • Data analysis and data science tools
  • Vehicle data quality dimensions
  • Analytic models development
  • Real-time data transactions analysis

Nice-to-have

  • Strong problem-solving skills
  • Strong communication skills
  • Adapt to Waterfall/Agile methodologies
  • Understand business/technical process flows

Key Requirements

  • Familiarity with statistics
  • Knowledge of Kafka streaming systems
  • Microservices Architecture knowledge
  • Cloud ecosystems architectural tenets
  • ETL methodologies across multiple product ecosystems
  • Experience with data in Microsoft Azure
  • Business intelligence and data analysis software
  • Database management system software knowledge
  • Unix skills – Shell scripting
  • Expert in using SQL

Work Rights

Not specified

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