Onstar Vehicle Data System Engineer

gmoshawa.ca

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.
  • The individual is responsible for providing technical expertise to develop analytics that meets the data quality 5 dimensions: Accuracy, Completeness, Reliability, Relevance, and Timeliness of Data within products/platforms.
  • GM is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging, believing that providing an inclusive workplace creates an environment in which employees can thrive.

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
  • data quality 5 dimensions
  • analytic models
  • automated data quality monitoring

Nice-to-have

  • customer experience understanding
  • multi-disciplinary and cross organizational team
  • innovative plans and solutions
  • enterprise data ecosystems
  • meaningful change through words and deeds

Key Requirements

  • Familiarity with statistics
  • Knowledge of Kafka streaming systems
  • Microservices Architecture understanding
  • Cloud ecosystems architectural tenets
  • ETL methodologies experience
  • 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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