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# Data Engineer - Data Software Engineering and Cloud Platforms, Early Career

- **Company:** General Motors
- **Location:** Warren, MI, United States
- **Salary:** $84,900.0 - $130,500.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Amazon Web Services, Microsoft Azure, Big Data, Cloud Computing, Computer Programming, Databases, Computer Engineering, Information Engineering, Extract Transform Load (ETL), Data Systems, Database Queries, Linux, Python (Programming Language), Software Engineering, Cloud Platform System, Snowflake, Git, Information Technology, Data Programming, Data Pipelines, Databricks
- **Published:** September 18, 2026
- **Apply:** https://dejobs.org/x/x/341FB52BFF21406392E33471786E6270/job/

## About the Role

· Pursuit of a bachelor's degree in one of the following areas: Computer Science, Software Engineering, Electrical/Computer Engineering, Information Technology or related degree

· Able to work fulltime, 40 hours per week

What Will Give You a Competitive Edge

· Strong SQL skills and familiarity with modern databases

· Basic programming experience in Python, Java, and/or Scala

· Understanding of data modeling concepts and ETL processes

· Excellent problem-solving and communication skills

· Eagerness to learn and grow in a collaborative environment

· Familiarity with cloud platforms (AWS, GCP, or Azure) and data engineering platforms (Databricks / Snowflake) and Git and basic Linux/CLI is a plus

## Description

The GM Data Engineering team is seeking early career candidates to help build large scale data platforms on cloud environments. The ideal applicants for these roles have a bachelor's degree in software engineering, computer science, mathematics, information technology or similar.

What You'll Do:

· 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


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