Data Engineering Manager – Hybrid, AI-Driven Leader

GM Financial; Irving (TX); Hybrid; USD 120,000 - 150,000; Full time

Benefits offered by this job

401K matching

Parental leave (12 weeks, 100% paid)

Tuition assistance

GM employee discount

Company holidays

Job summary

GM Financial is expanding its data engineering capabilities with a hybrid role that blends on-site and remote work across a large data ecosystem. You will design and deploy scalable data pipelines, enabling batch and streaming processing to support AI-driven analytics and decision making.

You will collaborate with data scientists and IT teams, implement automated data workflows, and ensure robust security and performance.

Qualifications

• Bachelors degree or equivalent required; strong foundation in data engineering.
• Experience with large data ecosystems and distributed processing platforms.
• Knowledge of Hadoop, Spark, and data security best practices.
• Experience with containerization and orchestration tools.
• Experience with scripting and automation.
• Familiarity with ETL/BI technologies is a plus.

Responsibilities

• Design and implement scalable data pipelines for batch and streaming workloads.
• Collaborate with data scientists, engineers, and IT to deploy data solutions.
• Code, test, and document data processing components.
• Maintain monitoring and support for data infrastructure and ETL processes.
• Contribute to end-to-end architecture for data platforms.
• Ensure security, reliability, and performance of data systems.

Skills

Hadoop

Spark

Security

Networking

Distributed systems

Linux/Unix

Cloud security

AI tools awareness

Education

Bachelor’s Degree in related field or equivalent

High School Diploma

Tools

Docker

Kubernetes

Mesos

Puppet

Chef

Ansible

Job description

GM Financial is expanding its data engineering capabilities with a hybrid role that blends on-site and remote work across a large data ecosystem. You will design and deploy scalable data pipelines, enabling batch and streaming processing to support AI-driven analytics and decision making.

You will collaborate with data scientists and IT teams, implement automated data workflows, and ensure robust security and performance.