Cloud Data Engineer — ETL & Data Platforms (Hybrid)

General Motors; Austin (TX); Hybrid; USD 85,000 - 131,000; Full time

Benefits offered by this job

Health benefits

Tuition assistance

GM vehicle discounts

Paid vacation

Job summary

General Motors is seeking an early-career Data Engineer in a hybrid role based in Austin, TX, with offices also in Warren, MI and Seattle, WA. A bachelor’s degree in software engineering, computer science, mathematics, information technology or related field is preferred.

You will design and migrate on-prem data systems to cloud environments while focusing on security and scalable data solutions. You will collaborate with data engineers and scientists to understand data needs, build ETL/ELT

Qualifications

• 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

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

Skills

SQL

Python

Java

Scala

Data modeling

Cloud platforms

Databricks

Snowflake

Education

Bachelor’s degree in software engineering, computer science, mathematics, information technology or similar

Tools

AWS

GCP

Azure

Job description

General Motors is seeking an early-career Data Engineer in a hybrid role based in Austin, TX, with offices also in Warren, MI and Seattle, WA. A bachelor’s degree in software engineering, computer science, mathematics, information technology or related field is preferred.

You will design and migrate on-prem data systems to cloud environments while focusing on security and scalable data solutions. You will collaborate with data engineers and scientists to understand data needs, build ETL/ELT