Senior Data Engineer

Stellantisfinancialservices; Auburn Hills (MI); On-site; USD 120,000 - 180,000; Full time

Job summary

Stellantis Financial Services is seeking a Senior Data Engineer to join the Supply Chain AI Hub. You will help turn AI ambition into reliable data foundations, design data models and pipelines, and promote governance and traceability to support analytics and deployment.

Collaborate with business, engineering and ICT stakeholders, own a defined subset of data engineering scope, and drive scalable, reusable data‑engineering practices across Supply Chain.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, Engineering, Mathematics, or related field
• 8 years of experience in data engineering or data platforms
• Previous Supply Chain experience
• Hands‑on experience with modern data platforms such as Databricks, Spark, Snowflake, or equivalent
• Experience with data pipelines, integration, semantic, lineage, architecture and platform environments
• Enterprise‑scale data transformation and delivery experience
• Ability to collaborate effectively with analytics, AI, and software engineering teams

Responsibilities

• Design, improve or govern data models, transformation logic and pipeline components that support AI and analytics use cases
• Promote maintainable structures, reusable components and clear lineage across transformations where relevant
• Support delivery teams with practical data‑engineering discipline rather than one‑off technical builds
• Clarify selected source‑to‑platform pathways, integration dependencies and technical constraints affecting delivery
• Help maintain visibility on traceability, handoffs and access conditions across Supply Chain
• Work with ICT and engineering stakeholders to keep the build path practical and scalable
• Contribute to selected quality checks, certification routines, governance expectations or compliance‑related traceability needs depending on the scope assigned
• Help surface structural data issues, documentation gaps or control weaknesses that affect deployment readiness
• Support a trusted delivery environment by making data assets more visible, understandable and supportable

Skills

Data modelling

Pipelines

Integration

Data quality

Data governance

SQL

Stakeholder management

Ownership

Education

Bachelor’s or Master’s degree in Computer Science / Data Engineering / Information Systems / Engineering / Mathematics

Tools

Databricks

Spark

Snowflake

Job description

About the Role

Join the Supply Chain AI Hub as a Senior Data Engineer helping turn AI ambition into reliable data foundations and delivery-ready assets. This role helps engage business, engineering and ICT stakeholders around practical data needs and constraints, scale AI delivery through stronger data models, pipelines, integration pathways, quality routines and traceability, and pioneer more robust data‑engineering practices that make solutions easier to trust, operate and industrialize.

Your Missions:

Data Modelling, Pipelines & Reuse:

• Design, improve or govern selected data models, transformation logic and pipeline components that support AI and analytics use cases
• Promote maintainable structures, reusable components and clear lineage across transformations where relevant
• Support delivery teams with practical data‑engineering discipline rather than one‑off technical builds

Platform, Integration & Traceability:

• Clarify selected source‑to‑platform pathways, integration dependencies and technical constraints affecting delivery
• Help maintain visibility on traceability, handoffs and access conditions across Supply Chain
• Work with ICT and engineering stakeholders to keep the build path practical and scalable

Data Quality, Certification & Governance Support:

• Contribute to selected quality checks, certification routines, governance expectations or compliance‑related traceability needs depending on the scope assigned
• Help surface structural data issues, documentation gaps or control weaknesses that affect deployment readiness
• Support a trusted delivery environment by making data assets more visible, understandable and supportable

Your Profile:

• Strong data‑engineering experience in modern enterprise environments, with depth in some combination of data modelling, pipelines, integration, quality, lineage or governance‑related topics
• Able to operate across business needs, technical constraints and delivery realities
• Strong SQL and practical understanding of data structures, transformations, traceability and controlled delivery environments
• Comfortable working with multiple stakeholders across architecture, data, engineering and governance topics
• Structured, pragmatic and able to take ownership of a defined subset of a broader senior data‑engineering scope

Skills You’ll Grow:

• Broader exposure across the different building blocks that make AI‑ready data operational at scale
• Experience working at the intersection of data engineering, integration, quality and delivery governance
• Opportunity to deepen expertise in a specific component while contributing to a wider AI data foundation agenda

Why Join / Impact:

• Work on data‑engineering challenges directly tied to real AI deployment in Supply Chain
• Join a role broad enough to offer variety, while still allowing focused ownership on a defined perimeter
• Help strengthen the data foundations that make scalable AI delivery possible

Basic Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, Engineering, Mathematics, or related field
• 8 years of experience in data engineering or data platforms
• Previous Supply Chain experience
• Hands‑on experience with modern data platforms such as Databricks, Spark, Snowflake, or equivalent
• Experience with data pipelines, integration, semantic, lineage, architecture and platform environments
• Enterprise‑scale data transformation and delivery experience
• Ability to collaborate effectively with analytics, AI, and software engineering teams