Senior Feature Engineer

General Motors

. Lead the design, development, and operation of GM’s governed feature platform .

Posted 11/6/2026full-timeUnited StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in feature engineering and data engineering, with a strong focus on building scalable ML/AI pipelines using Python, SQL, and Databricks. Proficient in implementing CI/CD practices and ensuring data quality for optimal model performance.

Highest-signal resume keywords

Feature EngineeringDatabricksPython ProgrammingCI/CD Pipeline DevelopmentData Quality Management

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Feature EngineeringPython ProgrammingSQLApache SparkDatabricksCI/CD PipelinesData Quality ChecksModular Pipeline DesignDelta LakeMonitoring and Alerting

Soft Skills

Strong Communication SkillsCross-Functional Collaboration

Tools & Technologies

DatabricksApache SparkGitKafkaDelta LIVE Tables

Industry Keywords

AI/ML Model DevelopmentData EngineeringFeature StoreReal-Time Data StreamingVehicle Telematics

Tech Stack

Tools & technologies

ApacheKafkaPandasPySparkPythonSparkSQLUnity

About the role

Key responsibilities & impact

Lead the design, development, and operation of GM’s governed feature platform
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, including notebooks, jobs, Delta Lake, and Unity Catalog
Collaborate with data scientists and ML engineers to translate modeling requirements into reusable features
Establish and maintain a feature store or equivalent for feature reuse, versioning, and train/serve parity
Implement CI/CD pipelines with automated testing, deployment, and rollback
Define and enforce data quality checks, including completeness, freshness, schema validation, drift detection, and anomaly detection
Optimize Spark and 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 integrate features with upstream data sources and downstream ML platforms
Monitor production feature pipelines and proactively resolve data quality or pipeline failures

Requirements

What you’ll need

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, including Spark clusters, notebooks, Delta Lake, and workflows/jobs
Proficiency in Python, including pandas, PySpark, and modular pipeline design
Strong SQL skills for complex data transformation, aggregation, and optimization
Working knowledge of Apache Spark, including PySpark or Spark SQL, for distributed data processing at scale
Experience building and maintaining CI/CD pipelines for data/ML pipeline code
Experience implementing data quality management practices, validation frameworks, monitoring, and alerting
Understanding of ML workflows and how feature quality impacts model performance
Experience with Git and collaborative software development practices
Strong communication skills and ability to work cross-functionally with data science, ML engineering, and platform teams
Must not require GM immigration sponsorship now or in the future, including H-1B, OPT, STEM OPT, CPT, TN, J-1, or other immigration support
8+ years of experience in data engineering (preferred)
Experience with vehicle telematics, battery health data, or embedded systems (preferred)
Familiarity with machine learning workflows and model deployment (preferred)
Experience with real-time data streaming technologies such as Kafka or Delta LIVE Tables (preferred)

Benefits

Comp & perks

Benefits and Total Rewards resources
Reasonable accommodations for applicants with disabilities
Inclusive workplace and equal employment opportunities
No relocation benefits; relocation costs are the selected candidate’s responsibility