Senior Data Engineer

General Motors (GM)

Confirmed live 2 days ago High trust
Closes in 4 days Hybrid

Quick summary

Work type
Hybrid
Location
Austin, TX
Salary
$119,200–$175,450 / yr
Posted
10 days ago
Freshness
Confirmed live 2 days ago
Closes
Sep 15, 2026 (soon)

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $176k
This role $147k
$108k most similar roles pay here $222k

This role pays less than 72% of similar roles. Most pay $140,262–$211,200 — the shaded band above. At the midpoint, this role pays about $147k versus about $176k 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 116 open roles on FindRole.

Listed pay typically runs $160,200–$245,000 across 59 roles with salary data.

Most-posted roles

View all roles at General Motors (GM)

At a glance

TL;DR · Senior Data Engineer

As a Senior Data Engineer, you will join the team to build next-generation telematics data products that power analytics, artificial intelligence, and decision-making across the enterprise. You will design, build, and productionize secure, scalable batch and streaming data pipelines in Azure Databricks and cloud environments. Your daily work involves transforming complex telemetry data from multiple source systems into trusted, well-structured datasets using Apache Spark, Delta Lake, and medallion architecture. To succeed, you must be proficient in Python or Scala, advanced SQL, and Unix/Linux while utilizing tools like Azure Data Lake, Kubernetes, and various data formats including JSON, Parquet, Avro, and XML. You will solve the challenge of replacing duplicated analytical logic with governed, reusable data products to provide a common foundation for connected vehicle insights regarding performance, safety, and operations.

What does a Data Engineer earn?

Median $183138 from 214 postings across 58 companies.

See salary data

What you'll do

  • Design and productionize secure, scalable batch and streaming data pipelines using Azure Databricks and Spark.
  • Transform raw telemetry from multiple source systems into structured, analytics-ready datasets for AI and machine learning.
  • Develop and optimize ETL/ELT workflows utilizing Delta Lake and medallion architecture.
  • Create governed data products, including reusable APIs and semantic layers, to enable self-service analytics.
  • Build feature-ready and model-ready datasets to support GenAI applications and data science experimentation.
  • Implement data quality, lineage, monitoring, and security controls to ensure reliable and compliant data products.
  • Improve engineering processes by enhancing automation, platform performance, and cost efficiency.
  • Troubleshoot production issues and maintain the reliability of the overall data platform operations.

What we're looking for

  • Bachelor's degree in computer science, software engineering, data science, or a related field, or equivalent experience.
  • 5+ years of relevant experience in data engineering, software engineering, or a related discipline.
  • Experience supporting AI and machine learning through feature engineering, model-ready data, and experimentation workflows.
  • Experience building GenAI, retrieval-augmented generation, natural-language analytics, or self-service data tools.
  • Proficiency in Python or Scala, advanced SQL, and Unix/Linux environments.
  • Hands-on experience with Databricks, Apache Spark, Delta Lake, and distributed data processing.
  • Experience with cloud data services including Azure Data Lake, Azure Kubernetes Service, or AWS EMR.
  • Experience with workflow orchestration, CI/CD, infrastructure as code, and data observability.

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