The Global Purchasing Business Analytics Team at Stellantis is seeking a Ontology 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 ResponsibilitiesDevelop, optimize, and maintain SQL /PySpark-based data models to support analytical applications in Global PurchasingPartner with data analysts to understand analytical requirements and translate them into well-structured backend data solutionsImplement data validation, transformation, and automation logic to ensure high data qualityWrite 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 applicableBasic QualificationsBachelor of Science degree in Business, Business Administration, Supply Chain Management, Finance, Marketing, Economics, International Business, Accounting, Entrepreneurship, Engineering, or equivalent; Other technical degrees with business background also considered8 + years of experience in data engineering or related experienceStrong SQL coding skillsFamiliarity with modern data platforms (e.g., Snowflake, Palantir Foundry, Databricks, etc.)Experience with data modeling concepts, star/snowflake schemas, and analytics-ready data designAbility to write clean, maintainable code and troubleshoot performance issues in large datasetsComfortable 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.Preferred QualificationsProficiency in PythonExperience with TypeScript, especially in the context of Palantir or similar platformsFamiliarity with Power BI, but focused on backend data support rather than report creationExposure to AI/ML workflows or interest in supporting such projectsExperience working in Agile and/or cross-functional teams#J-18808-Ljbffr