Data Engineer - Supply Chain

StellantisAuburn Hills, MI

About The Position

We are building an AI-enabled supply chain that senses, predicts, prescribes, and acts. The Data Engineer plays a critical role in enabling this vision by designing, building, and operating enterprise-grade data pipelines and analytical data products that power advanced analytics, optimization, automation, and agentic AI solutions across the Supply Chain organization. This role focuses on production-ready data engineering-ensuring data is reliable, governed, scalable, and fit for decisioning. The Data Engineer partners closely with Data Science, AI Engineering, Automation, and Platform teams to deliver high-quality data assets embedded into operational workflows.

Requirements

  • Bachelor’s in Computer Science, Information Systems, or a related field required
  • 8+ years of professional experience in data engineering, analytics engineering, or data platform development
  • Strong proficiency in Python and SQL for data transformation and pipeline development
  • Experience designing and maintaining production-grade data pipelines and analytical data models
  • Hands-on experience with modern data platforms such as Databricks, Spark, Snowflake, or equivalent
  • Solid understanding of data quality, validation, and monitoring concepts
  • Experience working with structured and semi-structured data at scale
  • Proven ability to own production data pipelines end-to-end (design → deployment → monitoring → incident response)
  • Demonstrated ability to operate independently, drive technical decisions, and deliver solutions in ambiguous environments with minimal oversight
  • Ability to collaborate effectively with analytics, AI, and software engineering teams

Nice To Haves

  • Master’s Degree
  • Experience supporting machine learning or advanced analytics pipelines, including feature engineering and model scoring data
  • Experience with orchestration tools, CI/CD, and version control for data pipelines
  • Familiarity with streaming or event-driven data architectures
  • Experience working with supply chain, operations, manufacturing, or ERP data
  • Knowledge of data governance, metadata management, and lineage tools
  • Experience supporting BI or downstream analytics tools (e.g., Power BI) and enterprise data platforms (e.g. Palantir Foundry)

Responsibilities

  • Design, build, and maintain scalable batch and near-real-time data pipelines supporting supply chain analytics and AI use cases
  • Ingest, transform, and curate data from enterprise and operational systems (ERP, planning, logistics, manufacturing, execution platforms)
  • Develop and maintain analytical data models and feature-ready datasets to support data science, optimization, and agentic AI workflows
  • Implement data quality validation, monitoring, and alerting to ensure trust and reliability of downstream analytics
  • Optimize data pipelines and storage for performance, cost, and scalability
  • Partner with data scientists and AI engineers to support model training, scoring, and deployment needs
  • Establish and follow best practices for data modeling, naming conventions, version control, and documentation
  • Ensure data solutions comply with enterprise standards for security, privacy, lineage, and governance
  • Support production operations, including incident investigation and root cause analysis related to data issues
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