Cloud Data Engineer - Early Career Path

General Motors; Warren (MI); Hybrid; USD 85,000 - 131,000; Full time

Benefits offered by this job

Health benefits

Relocation assistance

Job summary

General Motors is seeking early career Data Engineering candidates to help build large-scale data platforms on cloud environments. The role requires a bachelor’s degree in CS/SE/IT or related fields and the ability to work full-time.

The team focuses on migrating on-premises data systems to cloud environments with emphasis on data security and privacy. You will collaborate with data engineers and data scientists to deliver scalable data solutions, design operational and analytic datastores, and

Qualifications

• Pursuit of a bachelor's degree in Computer Science, Software Engineering, Electrical/Computer Engineering, Information Technology or related degree.
• Able to work fulltime, 40 hours per week.

Responsibilities

• Lead the design and development of migrating on-prem data systems to cloud environments
• Design data solutions around current and future data security and privacy requirements
• Work with data engineers and data scientists to understand data needs and deliver solutions
• Build and maintain operational and analytic datastores
• Assist in designing, developing, and maintaining ETL/ELT pipelines
• Document processes and contribute to knowledge sharing within the team
• Learn how to optimize cloud compute and storage cost

Skills

SQL skills

Python

Java

Scala

Cloud platforms

ETL/ELT design

Education

Bachelor's degree in CS/SE/IT

Tools

Databricks

Snowflake

Git

Linux/CLI

Job description

General Motors is seeking early career Data Engineering candidates to help build large-scale data platforms on cloud environments. The role requires a bachelor’s degree in CS/SE/IT or related fields and the ability to work full-time.

The team focuses on migrating on-premises data systems to cloud environments with emphasis on data security and privacy. You will collaborate with data engineers and data scientists to deliver scalable data solutions, design operational and analytic datastores, and