Senior Data Engineer

General Motors (GM)

Remote Hybrid

Quick summary

Work type: Remote
Location: Warren, MIAustin, TX
Salary: $138,700–$175,450 / yr
Posted: 5 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $170k

This role $157k

$126k most similar roles pay here $224k

This role pays less than 66% of similar roles. Most pay $136,050–$203,712 — the shaded band above. At the midpoint, this role pays about $157k versus about $170k for comparable roles.

Based on 240 similar postings.

Employer

About General Motors (GM)

General Motors (GM) is a leading American multinational automotive corporation founded in 1908 and headquartered in Detroit, Michigan.

General Motors (GM) currently has 123 open roles on FindRole.

Listed pay typically runs $160,200–$261,300 across 73 roles with salary data.

Most-posted roles

View all roles at General Motors (GM)

At a glance

TL;DR · Senior Data Engineer

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Join our senior data engineering team at the Global Technical Center or Austin Technical Center as a Level 7 individual contributor, where you will independently lead complex technical projects and enhance processes across the organization. You’ll design and build reliable, scalable data pipelines in Azure Databricks to support AI and analytics use cases, transforming raw data into high-quality datasets for model development. Collaborate closely with data scientists, analysts, and business teams to ensure data accessibility and alignment with business outcomes, while also mentoring less experienced team members. Key skills include experience with Python or Scala, SQL, cloud platforms like Azure, Databricks (Apache Spark), Delta Lake, and a strong understanding of statistics and machine learning concepts. This role demands expertise in building scalable batch and streaming pipelines, supporting AI use cases through data foundations, and driving technical direction within the team.

Skills

Azure Databricks Python Scala SQL Apache Spark Delta Lake Azure AWS GCP NoSQL ETL frameworks Key-value datastores Document stores CI/CD Prometheus Kubernetes Terraform PostgreSQL Mentorship

What you'll do

Design and build reliable, scalable data pipelines in Azure Databricks for AI and analytics.
Transform raw data from multiple sources into high-quality datasets for downstream use.
Drive process improvements to enhance team efficiency and support broader functional strategy.
Solve complex data engineering problems using advanced analytical techniques with strong ownership.
Partner closely with data scientists, analysts, and business teams to ensure data accessibility and trustworthiness.

What we're looking for

5+ years of data engineering experience with expertise in pipeline development and production support.
Strong proficiency in Python/Scala, SQL, and cloud platforms (Azure preferred).
Experience designing and optimizing scalable batch and streaming data pipelines using Databricks/Apache Spark.
Ability to independently manage complex technical challenges and deliver solutions with minimal guidance.
Demonstrated success collaborating across engineering, analytics, and business teams for measurable outcomes.
Understanding of statistics, machine learning concepts, and ability to support model development workflows.

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