Data Engineer

Stellantisfinancialservices; Auburn Hills (MI); On-site; USD 80,000 - 110,000; Full time

Job summary

Stellantisfinancialservices is seeking a Data Engineer in Auburn Hills, Michigan. This role demands a finance or cost engineering background coupled with hands-on experience in data engineering. You will be pivotal in delivering modern analytics and AI-enabled solutions, managing cross-functional projects across cloud platforms like Snowflake, AWS, and Azure.

The ideal candidate has a Bachelor's degree in Computer Science, along with 3+ years of experience in technical project delivery. Strong organizational skills and the ability to navigate ambiguity are essential.

Qualifications

• 3+ years of professional experience in technical project delivery, data engineering, or analytics platform implementation.
• Finance or costing background with understanding of cost drivers, financial models, or cost engineering processes.
• Experience with cloud database environments such as Snowflake, AWS, or Azure.

Responsibilities

• Drive delivery of modern analytics, automation, and AI-enabled solutions.
• Manage end-to-end project execution while working closely with business and ICT partners.
• Deliver scalable, secure, and high-impact data products.

Skills

Project management skills

Data engineering exposure

Communication skills

Analytical mindset

Education

Bachelor’s degree in Computer Science or related field

Tools

Snowflake

AWS

Azure

Databricks

Microsoft Power Platform

Job description

Data Engineer – Cost Methods, Tools & Data Solutions (CMTD)

Cost Methods, Tools & Data Solutions (CMTD) is seeking a Data Engineer with a finance or cost engineering background and hands‑on data engineering experience to drive delivery of modern analytics, automation, and AI‑enabled solutions. This role will lead cross‑functional initiatives across cloud data platforms (Snowflake, AWS, Azure), Databricks, Palantir Foundry, and the Microsoft Power Platform (Power Apps, Power Automate, Power BI, Dataverse). The ideal candidate combines strong project‑management discipline with technical fluency and an understanding of automotive cost engineering, finance, and purchasing data.

You will manage end‑to‑end project execution while working closely with business and ICT partners to deliver scalable, secure, and high‑impact data products. Experience with agentic AI chatbot development, Generative AI, and Microsoft Copilot is strongly preferred.

Basic Qualifications

• Bachelor’s degree in Computer Science (or a related technical field).
• 3+ years of professional experience in technical project delivery, data engineering, or analytics platform implementation.
• Demonstrated project management skills: planning, execution, stakeholder management, risk management, and delivery governance.
• Finance or costing background with understanding of cost drivers, financial models, or cost engineering processes.
• Data engineering exposure: pipelines, transformations, data modeling concepts, and working with data engineering teams.
• Experience with one or more cloud database environments such as Snowflake, AWS, or Azure.
• Hands‑on development and experience with Snowflake, AWS, Azure, Databricks, Palantir Foundry, SQL, and the Microsoft Power Platform.

Preferred Qualifications

• Automotive industry experience, particularly in cost engineering, manufacturing, or product development.
• Experience with agentic AI chatbot development or internal AI assistants.
• Knowledge of Generative AI and familiarity with Microsoft Copilot capabilities and adoption strategies.
• Experience with enterprise governance for analytics platforms.
• Familiarity with Agile delivery (Scrum/Kanban), DevOps concepts, and structured release management.

Skills & Competencies

• Strong communication skills: ability to explain technical details to non‑technical stakeholders and align decisions quickly.
• Highly organized with strong attention to detail; effective at managing ambiguity and changing priorities.
• Ability to influence across teams without direct authority; strong facilitation and conflict resolution skills.
• Analytical mindset with comfort interpreting data issues (reconciliation, validation, root‑cause analysis).
• Customer‑focused approach: understands end‑user workflow pain points and drives practical, adoptable solutions.
• Passion for digital transformation, automation, and AI‑driven solutions.