Stellantis is a leading global automaker and mobility provider that offers clean, connected, affordable and safe mobility solutions. Our Company’s strength lies in the breadth of our iconic brand portfolio, the diversity and passion of our people, and our deep roots in the communities in which we operate. Our ambitious electrification and software strategies and the creation of an innovative ecosystem of strategic, game-changing partnerships are driving our transformation to a sustainable mobility tech company.
The driving force behind us is the diverse and talented group of men and women around the world who bring their passion and experience to their work every day. And while we are a truly global organization, we remain deeply rooted in the communities in which we operate and where our colleagues live and work.
With industrial operations in nearly 30 countries, Stellantis could consistently exceed the evolving needs and expectations of consumers in more than 130 markets, while creating superior value for all stakeholders.
Please submit your CV in English.
Position Overview
The Global Purchasing Business Analytics Team at Stellantis is seeking a Data Engineer to build and maintain robust backend data solutions in support of global purchasing analytics. This role is focused on designing scalable data models and developing high-quality, production-grade code in SQL and Python to support our enterprise analytics architecture. You will work across platforms such as Snowflake, Palantir Foundry, Power BI, and potentially Databricks, helping the team evolve toward advanced capabilities, including AI-enhanced insights. While you’ll collaborate closely with analysts and business stakeholders, this is a data engineering position - not a dashboard/reporting development role. As Stellantis operates globally with diverse and region-specific systems, you will often need to integrate fragmented data sources and iteratively develop solutions without complete documentation or available SMEs. Success in this role requires initiative, curiosity, and a self-starting mindset - someone who can function as a data entrepreneur: discovering and connecting data across domains to drive business value in a complex enterprise environment. You will work on a globally distributed team. Working hours must include at least 4 hours of overlap with Eastern Standard Time (EST) to ensure strong collaboration.
Key Responsibilities
- Develop, optimize, and maintain SQL / PySpark-based data models to support analytical applications in Global Purchasing .
- Partner with data analysts to understand analytical requirements and translate them into well-structured backend data solutions .
- Implement data validation, transformation, and automation logic to ensure high data quality
- Write clean, efficient, and maintainable code using SQL, Python/PySpark, and TypeScript (where applicable).
- Explore and connect new or unfamiliar datasets in an iterative and self-directed manner, especially where formal documentation or SMEs are unavailable.
- Collaborate with cross-functional teams to connect complex data into usable data models.
- Contribute to the adoption of AI-driven tooling and workflows where applicable.
Required Qualifications
- Strong SQL and Python coding skills.
- A least 5 years experience in Ontology or Data Engineering.
- Familiarity with modern data platforms (e.g., Snowflake, Palantir Foundry, Databricks, etc.).
- Experience with data modeling concepts, star/snowflake schemas, and analytics-ready data design.
- Ability to write clean, maintainable code and troubleshoot performance issues in large datasets.
- Comfortable working in a backend engineering role, supporting front-end dashboards without directly building reports.
- Solid understanding of data pipelines, ETL/ELT workflows, and version control (e.g., Git).
- Strong self-learning skills and ability to work independently in ambiguous, data-discovery-driven scenarios.
At Stellantis, we assess candidates based on qualifications, merit and business needs. We welcome applications from people of all gender identities, age, ethnicity, nationality, religion, sexual orientation and disability. Diverse teams will allow us to better meet the evolving needs of our customers and care for our future.
