Senior Data Engineer

General Motors (GM)

Confirmed live today High trust

Hybrid

Quick summary

Work type: Hybrid
Location: Austin, TX
Employment: Full-time
Posted: 123 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $164k

$110k $212k

below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $126,800–$202,120.

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 196 open roles on FindRole.

Listed pay typically runs $159,200–$245,000 across 54 roles with salary data.

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At a glance

TL;DR · Senior Data Engineer

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The Senior Data Engineer joins the team to design and develop batch and streaming ETL/ELT pipelines within Azure Databricks. This role involves building reusable Bronze, Silver, and Gold data pipelines, data quality frameworks, and governed data products using Unity Catalog. The engineer will operationalize ML workflows for feature engineering, model training, and deployment while establishing MLflow-based lifecycle controls for experiment tracking and versioning. Key responsibilities include implementing CI/CD pipelines with Git-based practices and supporting the modernization of legacy workflows into cloud-native patterns. Required technical skills include proficiency in Scala, Python, SQL, Spark, and Databricks. The work focuses on manufacturing and enterprise data, specifically addressing industrial IoT, plant-floor data, and quality analytics to transition proof-of-concept solutions into scalable, production-ready environments.

What does a Data Engineer earn?

Median $159000 from 203 postings across 58 companies.

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Skills

Databricks Python SQL Spark Scala MLflow Unity Catalog CI/CD Git Azure Kafka Event Hub Java Structured Streaming DLT ETL ELT

What you'll do

Design and develop batch and streaming ETL/ELT pipelines in Azure Databricks.
Build reusable data pipelines, quality frameworks, and governed data products in Unity Catalog.
Build and operationalize ML workflows for data preparation, model training, and inference.
Establish and maintain MLflow-based model lifecycle controls including experiment tracking and versioning.
Implement CI/CD pipelines for data products and ML code using Git-based development practices.
Build and support Databricks jobs and workflows for orchestration and scheduled execution.
Improve production readiness through automated testing, monitoring, validation, and alerting.
Modernize legacy data and ML workflows into standardized cloud-native Databricks patterns.

What we're looking for

5+ years of relevant full-time experience or equivalent knowledge.
Bachelor’s degree in Computer Science, Data Science, Engineering, or a related technical field, or equivalent practical experience.
Strong proficiency in Scala, Python, SQL, Spark, and Databricks with production-quality software engineering practices.
Strong experience building and supporting cloud-based ETL/ELT pipelines, data platforms, and pipeline orchestration for batch and streaming operations.
Experience deploying machine learning models into production environments and supporting model development through operational release.
Strong experience with Databricks jobs, workflows, repos, Unity Catalog, and MLflow-based experimentation and model lifecycle management.
Experience building CI/CD pipelines with Git-based workflows, automated testing, and deployment of data or ML products.
Strong troubleshooting, communication, and cross-functional collaboration skills.