Data Engineer - Vehicle Configuration Optimization

Stellantis
United States, Michigan, Auburn Hills
Aug 21, 2026
We are seeking a Data Engineer to help build and scale the data foundation for our Vehicle Configuration Optimization (VCO) initiative. This role will focus on ingesting, transforming, and structuring data from enterprise systems (e.g., Snowflake data lake) into Databricks, enabling advanced analytics and modeling downstream. This is an ideal role for an engineer who thrives in building reliable, scalable data systems and wants to work at the intersection of automotive data and advanced analytics. Key Responsibilities: Build and maintain data pipelines that ingest data from Snowflake into Databricks Design and implement data transformations aligned to the medallion architecture (Bronze/Silver/Gold layers) Ensure pipeline health, stability, monitoring, and performance optimization Develop robust ETL/ELT workflows using Python and SQL Create clean, curated datasets to support analytics, simulation, and machine learning use cases Partner closely with data scientists, analysts, and business stakeholders to understand data needs Implement data quality checks, validation processes, and governance standards Basic Qualifications: Bachelor's Degree Minimum 5 years of experience in data engineering or similar role Exposure to automotive price and product datasets Strong hands-on experience with Databricks (critical requirement) Proficiency in SQL and Python Experience building and maintaining data pipelines and ETL processes Familiarity with cloud data platforms Solid understanding of data modeling and medallion architecture concepts Preferred Qualifications: Experience with Snowflake and data lake architectures Experience with Spark / PySpark Familiarity with pipeline orchestration and monitoring tools Understanding of downstream analytics or ML use cases We are seeking a Data Engineer to help build and scale the data foundation for our Vehicle Configuration Optimization (VCO) initiative. This role will focus on ingesting, transforming, and structuring data from enterprise systems (e.g., Snowflake data lake) into Databricks, enabling advanced analytics and modeling downstream. This is an ideal role for an engineer who thrives in building reliable, scalable data systems and wants to work at the intersection of automotive data and advanced analytics. Key Responsibilities: Build and maintain data pipelines that ingest data from Snowflake into Databricks Design and implement data transformations aligned to the medallion architecture (Bronze/Silver/Gold layers) Ensure pipeline health, stability, monitoring, and performance optimization Develop robust ETL/ELT workflows using Python and SQL Create clean, curated datasets to support analytics, simulation, and machine learning use cases Partner closely with data scientists, analysts, and business stakeholders to understand data needs Implement data quality checks, validation processes, and governance standards At Stellantis, we assess candidates based on qualifications, merit, and business needs. We welcome applications from all people without regard to sex, age, ethnicity, nationality, religion, sexual orientation, disability, or any characteristic protected by law. We believe that diverse teams reflect our identity as a global company, enabling us to better address the evolving needs of our customers and care for our future.