Software Engineer, Advanced Analytics

General Motors; Santa Fe (NM); Remote; USD 120,000 - 150,000; Full time

Job summary

General Motors is seeking a software engineer focused on analytics to join our Advanced Analytics team. You will contribute to end‑to‑end feature development, build Python services and TypeScript/React interfaces, and shape data pipelines across engineering systems.

As the embedded data software engineer, you will collaborate with data scientists and scale solutions using Kubernetes on Azure, CI/CD, and IaC, delivering reliable, observable production services for vehicle programs.

Responsibilities

• Contribute as part of a cross‑functional team to propose and implement data‑driven software and analytic solutions for engineering organizations.
• Build and deliver end‑to‑end features, including Python services, relational data models, and TypeScript/React interfaces.
• Develop and maintain data pipelines that integrate GM’s engineering systems of record into applications and data products.
• Collaborate with data scientists to operationalize analytical work and deliver it to end users through scalable products.
• Deploy and operate production systems using Kubernetes on Azure, CI/CD workflows, infrastructure as code, and modern observability practices.
• Partner with stakeholders across vehicle hardware, software and electronics, supplier quality, warranty, and program management.

Skills

Python

React

TypeScript

SQL

Data pipelines

Tools

Kubernetes

Azure

Databricks

CI/CD

Job description

Remote/Hybrid

Remote – United States

Warren, Michigan, United States of America

Full time

JR-202619438

Job Description

At General Motors, our product teams are redefining mobility. Through a human-centered design process, we create vehicles and experiences that are designed not just to be seen, but to be felt. We’re turning today’s impossible into tomorrow’s standard —from breakthrough hardware and battery systems to intuitive design, intelligent software, and next-generation safety and entertainment features.

Every day, our products move millions of people as we aim to make driving safer, smarter, and more connected, shaping the future of transportation on a global scale.

GM’s Advanced Analytics team turns the engineering organization’s data into decisions, then builds the software that puts those decisions in front of the people making them.

We do the analytics and data science: forecasting and statistical analysis of program execution, the KPIs engineering leadership runs the business on, curated Databricks data products across parts, bills of material, engineering changes, warranty, and resource demand, and a growing amount of AI tooling. Our partners span vehicle hardware engineering, software and electronics, supplier quality, warranty, and program management.

The Role

This role serves as the second software engineer on a rapidly growing portfolio, supporting end‑to‑end feature development. Work often begins with understanding how vehicle program stakeholders operate and extends through designing schemas, building APIs, developing interfaces, wiring data pipelines, and monitoring service‑level objectives after deployment.

Weekly work may span tuning Postgres query plans, building and refining React components, writing Databricks jobs, and adjusting Kubernetes manifests. As the software engineer embedded within a team of data scientists, the position is responsible for defining and executing how software solutions are built .

What You’ll Do (Responsibilities)

• Contribute as part of a cross‑functional team to propose and implement high‑impact, data‑driven software and analytic solutions for engineering organizations.

• Build and deliver end‑to‑end features, including Python services, relational data models, and TypeScript/React interfaces.

• Develop and maintain data pipelines that integrate GM’s engineering systems of record into applications and data products.

• Collaborate with data scientists to operationalize analytical work and deliver it to end users through scalable products.

• Deploy and operate production systems using Kubernetes on Azure, CI/CD workflows, infrastructure as code, and modern observability practices.

• Partner with stakeholders across vehicle hardware,