Senior Data Engineer — Telemetry Data Platform (Hybrid)

General Motors; Nacogdoches (TX); Hybrid; USD 119,000 - 175,000; Full time

Benefits offered by this job

Health benefits

GM vehicle discounts

Tuition assistance

Paid time off

Job summary

General Motors is seeking a hands-on Senior Data Engineer in Texas to design, build, and productionize secure, scalable data pipelines for telematics data. Hybrid work with three days onsite at Warren or Austin centers.

You will enable GenAI-ready datasets, governance, and reusable data products to accelerate analytics across the enterprise. Applicants should have 5+ years in data/software engineering, deep experience in Spark, Databricks, Delta Lake, and Python/Scala, plus cloud platforms and

Qualifications

• Bachelor's degree or equivalent experience in computer science, software engineering, data science, or a related field.
• 5+ years of data engineering or software engineering experience.
• Experience supporting AI/ML through feature engineering, model-ready data, or deployment.
• Experience building GenAI, retrieval-augmented generation or self-service data tools.
• Experience with cloud data services (Azure, AWS, or GCP) and data orchestration tooling.

Responsibilities

• Design, build, and productionize secure, scalable batch and streaming data pipelines.
• Transform data from multiple sources into trusted analytics-ready datasets.
• Develop ETL/ELT workflows using Spark, Delta Lake, and medallion architecture.
• Enable self-service analytics and GenAI through governed data products and APIs.
• Mentor engineers and contribute to engineering standards and documentation.

Skills

Python

Scala

Databricks

Apache Spark

Delta Lake

SQL

Education

Bachelor's degree in CS/related field

Tools

Azure Databricks

AWS EMR

Kubernetes

Job description

General Motors is seeking a hands-on Senior Data Engineer in Texas to design, build, and productionize secure, scalable data pipelines for telematics data. Hybrid work with three days onsite at Warren or Austin centers.

You will enable GenAI-ready datasets, governance, and reusable data products to accelerate analytics across the enterprise. Applicants should have 5+ years in data/software engineering, deep experience in Spark, Databricks, Delta Lake, and Python/Scala, plus cloud platforms and