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 Responsibilities include but not limited to:
- 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
Basic Qualifications:
- Bachelor 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 considered
- 8 + years of experience in data engineering or related experience
- Strong SQL coding skills
- 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.
Preferred Qualifications:
- Proficiency in Python
- Experience with TypeScript, especially in the context of Palantir or similar platforms
- Familiarity with Power BI, but focused on backend data support rather than report creation
- Exposure to AI/ML workflows or interest in supporting such projects
- Experience working in Agile and/or cross-functional teams
Skills Required
- Bachelor's degree in Business, Supply Chain, Finance, Economics, Engineering, or equivalent
- 8+ years of experience in data engineering or related experience
- Strong SQL coding skills
- Proficiency in Python
- Experience with PySpark
- Experience writing production-grade code and troubleshooting performance on large datasets
- Familiarity with modern data platforms (Snowflake, Palantir Foundry, Databricks)
- Experience with data modeling concepts (star/snowflake schemas) and analytics-ready design
- Solid understanding of data pipelines, ETL/ELT workflows, and version control (Git)
- Ability to explore and integrate fragmented or poorly documented datasets independently
- Ability to write TypeScript where applicable (especially in Palantir contexts)
- Work hours must include at least four hours overlap with Eastern Standard Time (EST)
- Familiarity with Power BI (backend support focus)
- Exposure to or interest in AI/ML workflows
- Experience working in Agile and/or cross-functional teams
Stellantis Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Stellantis and has not been reviewed or approved by Stellantis.
-
Pay Growth & Progression — Contract-driven increases lifted hourly wages roughly 25% over 4.5 years and restored cost-of-living adjustments, pushing top rates near $42 per hour by the end of the agreement. Union hourly positions appear to have benefited most since the 2023 deal.
-
Affordable Benefits — UAW-represented hourly workers pay no premiums and about 3% of total healthcare costs while receiving comprehensive medical, dental, vision, and wellness coverage. This creates materially lower out-of-pocket costs for represented hourly roles.
-
Retirement Support — Post-2007 hourly hires receive a 10% employer 401(k) contribution and legacy workers saw defined-benefit improvements with retiree bonuses. Salaried roles also cite a 401(k) with employer match and contribution up to a maximum of 8%.
Stellantis Insights
What We Do
Our storied and iconic brands embody the passion of their visionary founders and today’s customers in their innovative products and services: they include Abarth, Alfa Romeo, Chrysler, Citroën, Dodge, DS Automobiles, Fiat, Jeep®, Lancia, Maserati, Opel, Peugeot, Ram, Vauxhall and mobility brands Free2move and Leasys. Powered by our diversity, we lead the way the world moves – aspiring to become the greatest sustainable mobility tech company, not the biggest, while creating added value for all stakeholders as well as the communities in which we operate.
