Key Responsibilities:

Data Engineering & Pipeline Development:

Design, implement, and maintain robust data pipelines (ETL/ELT) to collect, process, and transform large-scale structured and unstructured datasets from diverse automotive sources.

Ensure data quality, integrity, and accessibility by developing automated validation and monitoring tools.

Optimize data workflows for performance, scalability, and reliability, supporting both batch and real-time analytics needs.

Collaborate with IT and analytics teams to integrate data from business systems into centralized data products.

Build, train, and deploy predictive models and machine learning algorithms for applications such as performance forecasting, anomaly detection, and customer segmentation.

Apply best practices in data visualization to ensure clarity, accuracy, and accessibility of insights, including interactive dashboards, automated reporting, and mobile-friendly solutions.

Collaboration & Stakeholder Engagement:

Serve as a technical liaison between HQ analytics and business teams, translating business needs into scalable data solutions.

Educate and mentor team members on data best practices, analytics tools, and emerging technologies.

Basic Qualifications:

Bachelor's degree in Computer Science, Data Engineering, Data Science, Information Systems, or a related field, or equivalent work experienceMinimum 1 year experience in data engineering, analytics, or data science (automotive industry experience preferred)Proficiency in programming languages such as Python and SQLHands-on experience with ETL/ELT tools, data modeling, and cloud platforms (Snowflake, etc.)Strong analytical thinking, problem-solving skills, and attention to detailExcellent communication and presentation abilities, with a proven ability to explain complex technical concepts to diverse audiencesAbility to manage multiple priorities and deliver results in a fast-paced environment

Preferred Qualifications:

Master Degree in Computer Science, Data Engineering, Data Science, Information Systems, or a related fieldDemonstrated experience designing and deploying business dashboards and data visualizations for large-scale automotive or after-sales operationsAdvanced proficiency with business intelligence tools (e.g., Power BI, Tableau, Qlik) and experience integrating visualizations with cloud data platforms (e.g., Snowflake)Familiarity with Mopar systems and performance metricsKnowledge of machine learning, deep learning, and advanced analytics techniquesCertifications in cloud data engineering or analytics platforms

Key Responsibilities:

Data Engineering & Pipeline Development:

Design, implement, and maintain robust data pipelines (ETL/ELT) to collect, process, and transform large-scale structured and unstructured datasets from diverse automotive sources.

Ensure data quality, integrity, and accessibility by developing automated validation and monitoring tools.

Optimize data workflows for performance, scalability, and reliability, supporting both batch and real-time analytics needs.

Collaborate with IT and analytics teams to integrate data from business systems into centralized data products.

Build, train, and deploy predictive models and machine learning algorithms for applications such as performance forecasting, anomaly detection, and customer segmentation.

Apply best practices in data visualization to ensure clarity, accuracy, and accessibility of insights, including interactive dashboards, automated reporting, and mobile-friendly solutions.

Collaboration & Stakeholder Engagement:

Serve as a technical liaison between HQ analytics and business teams, translating business needs into scalable data solutions.

Educate and mentor team members on data best practices, analytics tools, and emerging technologies.

At Stellantis, we assess candidates based on qualifications, merit, and business needs. We welcome applications from all people without regard to sex, age, ethnicity, nationality, religion, sexual orientation, disability, or any characteristic protected by law. We believe that diverse teams reflect our identity as a global company, enabling us to better address the evolving needs of our customers and care for our future. Equal Opportunity Employer Minorities/Women/Protected Veterans/Disabled.