Senior Data Engineer: Snowflake & DBT Pipelines

Stellantis; Torino; In loco; EUR 55.000 - 90.000; Tempo pieno

Descrizione del lavoro

Stellantis is seeking a Data Engineer in Torino to design, develop and maintain robust data pipelines supporting data-driven decisions across the organization. You will collaborate with Data Scientists, AI specialists and business teams to ensure reliable, scalable data delivery.

The role emphasizes production-grade data models, data quality checks and the ability to work in a global, complex environment within Global Supply Chain.

Competenze

• 5+ years of experience in Data Engineering or similar roles.
• Degree in Engineering, Computer Science or Computer Programming (Master's or PhD preferred).
• Strong programming skills in Python and SQL.
• Experience with Snowflake and a solid understanding of DBT.
• Basic knowledge of DevOps and orchestration tools (Git, CI/CD, Airflow).
• Experience designing and managing data pipelines in enterprise environments.

Mansioni

• Design, build, maintain and optimize data pipelines from multiple sources into clean, structured formats.
• Develop scalable, production-ready data models and transformations using Snowflake and DBT.
• Ensure data is stored, processed and delivered reliably and efficiently.
• Implement data quality checks and validation processes to ensure accuracy and integrity.
• Collaborate with Data & AI teams to support analytics and advanced data initiatives.
• Contribute to continuous improvement of data engineering standards, tools and processes.

Conoscenze

Python

SQL

Communication

Independent work

Formazione

Master's degree in Engineering or Computer Science

Strumenti

Snowflake

DBT

Git

CI/CD

Airflow

Descrizione del lavoro

Stellantis is seeking a Data Engineer in Torino to design, develop and maintain robust data pipelines supporting data-driven decisions across the organization. You will collaborate with Data Scientists, AI specialists and business teams to ensure reliable, scalable data delivery.

The role emphasizes production-grade data models, data quality checks and the ability to work in a global, complex environment within Global Supply Chain.