Senior Data Engineer

gmoshawa.ca

Austin, Texas, USA
Base: $129,400 - $212,300; bonus/equity: an incent...
Fully remote
Python or scala
Sql and relational/non-relational data storage
Distributed data processing (spark)
The Sr. Data Engineer role is responsible for designing, developing and maintaining data pipelines, databases and data infrastructure to enable the efficient data collection, storage and analysis in support of marketing strategies

Job Summary

  • The Sr. Data Engineer role is responsible for designing, developing and maintaining data pipelines, databases and data infrastructure to enable the efficient data collection, storage and analysis in support of marketing strategies.
  • This role requires collaboration with data scientists, data infrastructure architects and data consumption stakeholders to ensure the availability of high-quality data for insights and decision making.
  • GM offers a variety of health and wellbeing benefit programs, including medical, dental, vision, retirement savings plan, and paid vacation & holidays.

Matching Summary

The Sr. Data Engineer role is responsible for designing, developing and maintaining data pipelines, databases and data infrastructure to enable the efficient data collection, storage and analysis in support of marketing strategies.

Salary

Base: $129,400 - $212,300; Bonus/Equity: An incentive pay program offers payouts based on company performance, job level, and individual performance; Benefits: GM offers a variety of health and wellbeing benefit programs.

Skills & Requirements

Must-have

  • Python or Scala
  • SQL and relational/non-relational data storage
  • distributed data processing (Spark)
  • container orchestration (Kubernetes)
  • data streaming in Kubernetes and Kafka
  • cloud platforms (Azure preferred)

Nice-to-have

  • data governance, metadata management, or data quality
  • schema design and data contracts
  • handling various file formats
  • Databricks, Snowflake, or similar platforms

Key Requirements

  • Bachelor’s degree in Computer Science, MIS, Software Engineering, or related field
  • 5 - 7+ years of data engineering/development experience
  • 3+ years of experience as a data engineer
  • 3+ years of experience in distributed data processing (Spark)
  • 3+ years of experience in container orchestration (Kubernetes)
  • Proficiency in data streaming in Kubernetes and Kafka
  • Experience with cloud platforms – Azure preferred; AWS or GCP also considered

Work Rights

Not specified

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