Senior Feature Engineer - Feature Store & ML Pipelines

General Motors Company; Austin (TX); On-site; USD 120,000 - 190,000; Full time

Job summary

General Motors is seeking a Senior Feature Engineer to lead design, development, and operation of a governed feature platform and shared infrastructure for product analytics. You will translate data into reliable, production-grade features for data scientists and ML engineers, collaborating across data science, ML, and platform teams.

This role emphasizes building scalable pipelines, feature stores, and CI/CD, with Databricks and Spark expertise to enable train/serve parity and strong data

Qualifications

• 5+ years of experience in feature engineering, data engineering, or ML engineering roles supporting AI/ML model development.
• Bachelor's degree in Computer Science, Mechanical Engineering, Electrical Engineering, Data Analytics or equivalent degree
• Strong hands-on experience with Databricks(Spark clusters, notebooks, Delta Lake, workflows/jobs)
• Proficiency inPython for data pipeline and feature transformation development (pandas, PySpark, modular pipeline design)
• StrongSQLskills for complex data transformation, aggregation, and optimization
• Solid working knowledge ofApache Spark(PySpark or Spark SQL) for distributed data processing at scale
• Experience building and maintainingCI/CD pipelinesfor data/ML pipeline code
• Demonstrated experience implementingdata quality managementpractices validation frameworks, monitoring, and alerting
• Understanding of ML workflows and how feature quality impacts model performance
• Experience with version control (Git) and collaborative software development practices
• Strong communication skills and ability to work cross-functionally with data science, ML engineering, and platform teams

Responsibilities

• Design, develop, and maintain scalable feature engineering pipelines for ML/AI model development and production inference
• Build and manage feature transformation logic using Python, SQL, and Apache Spark across large, distributed datasets
• Develop and operate feature pipelines within Databricks (notebooks, jobs, Delta Lake, Unity Catalog)
• Collaborate with data scientists and ML engineers to translate modeling requirements into well-defined, reusable features
• Establish and maintain a feature store (or equivalent) to enable feature reuse, versioning, and consistency between training and inference (train/serve parity)
• Implement CI/CD pipelines for feature and data pipeline code — automated testing, deployment, and rollback for pipeline changes
• Define and enforce data quality checks (completeness, freshness, schema validation, drift detection, anomaly detection) across feature pipelines
• Optimize Spark/Databricks jobs for performance, cost, and reliability at scale
• Document feature definitions, lineage, and pipeline architecture for reproducibility and audit purposes
• Partner with data engineering and platform teams to ensure features integrate cleanly with upstream data sources and downstream ML platforms
• Monitor production feature pipelines and proactively resolve data quality or pipeline failures

Skills

Feature engineering

Data engineering

ML engineering

Python

SQL

Apache Spark

Git

CI/CD

Data quality

Cross-functional collaboration

ML workflows

Education

Bachelor's degree

Tools

Databricks

Delta Lake

Unity Catalog

Apache Spark

Job description

General Motors is seeking a Senior Feature Engineer to lead design, development, and operation of a governed feature platform and shared infrastructure for product analytics. You will translate data into reliable, production-grade features for data scientists and ML engineers, collaborating across data science, ML, and platform teams.

This role emphasizes building scalable pipelines, feature stores, and CI/CD, with Databricks and Spark expertise to enable train/serve parity and strong data