Data Engineering Manager

General Motors (GM)

Confirmed live yesterday High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Austin, TX
Posted
32 days ago
Freshness
Confirmed live yesterday

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Salary context

How this pay compares to similar roles

Similar $178k
$133k most similar roles pay here $228k

This listing doesn't post a salary. Most similar roles pay $141,800–$215,050.

Based on 240 similar postings.

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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.

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At a glance

TL;DR · Data Engineering Manager

The Data Engineering Manager leads a team of data engineers focused on building and operating customer data platforms for OnStar, Connected Services, Marketing, Personalization, AI, and Advanced Analytics. This role involves managing people, defining technical roadmaps, and overseeing the end-to-end delivery of scalable batch, streaming, API, and event-driven data pipelines. The manager will drive modernization from legacy systems to cloud-native, multi-cloud Lakehouse architectures while ensuring high standards for data observability, security, and cost efficiency. Key technologies include Databricks, Apache Spark, Delta Lake, Unity Catalog, Python, and SQL across Azure, AWS, and GCP environments. The role addresses the challenge of creating trusted, governed data products to power predictive analytics, Generative AI, and LLM applications within a complex customer data ecosystem, ensuring seamless interoperability across various cloud platforms for millions of connected experiences.

What you'll do

  • Lead, mentor, and manage a high-performing team of data engineers including hiring and performance management.
  • Define and execute technical roadmaps for customer, marketing, and digital data products across multi-cloud environments.
  • Architect and build scalable batch, streaming, and event-driven data pipelines using Databricks and Apache Spark.
  • Drive the migration of legacy platforms to cloud-native, multi-cloud Lakehouse architectures.
  • Build trusted, governed data products to support AI, machine learning, and generative AI applications.
  • Champion engineering excellence through CI/CD, infrastructure as code, and automated data quality testing.
  • Optimize platform performance, reliability, and cloud cost efficiency across Azure, GCP, and AWS.

What we're looking for

  • Bachelor’s degree in computer science, Engineering, Information Systems, or a related field.
  • 7+ years of experience in Data Engineering, Software Engineering, or production grade Distributed Data Platforms.
  • 3+ years of proven experience leading and managing data engineering or software engineering teams.
  • Deep expertise with Databricks, Apache Spark, Delta Lake, Unity Catalog, Python, SQL, and modern Lakehouse architectures.
  • Experience designing cloud-native solutions across Azure, AWS, or GCP.
  • Strong understanding of data modeling, governance, observability, security, and engineering best practices.
  • Experience or exposure to AI-first concepts including Generative AI, RAG, vector search, and LLM-powered applications.
  • Experience building large-scale distributed batch and streaming data pipelines.

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