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.
Equal Opportunity Employer Minorities/Women/Protected Veterans/Disabled.
