ICT Data Engineer

The ICT Data Engineer supports Purchasing and Finance Analytics and Programs within Stellantis North America Data & AI, building and maintaining data pipelines and data infrastructure to enable analytics offerings and data products.

Responsibilities

• Gather and integrate large, complex data sets that satisfy both functional and non functional requirements.
• Design, implement, and optimize end-to-end data pipelines for ingesting, processing, and transforming large volumes of structured and unstructured data.
• Develop robust ETL processes to consolidate data from diverse sources.
• Identify and implement internal process improvements, including infrastructure redesigns for scalability, optimized data delivery, and automation of manual tasks.
• Build the infrastructure necessary for efficient extraction, transformation, and loading from various sources using AWS, Azure, DB2, and SQL technologies.
• Create scalable data structures to provide actionable insights into key metrics such as operational efficiency and customer acquisition.
• Collaborate with stakeholders, including Data Product teams, to support data infrastructure needs and address data related technical issues.
• Design and maintain data models, schemas, and database structures supporting analytical and operational use cases.
• Optimize data storage and retrieval for performance and scalability.
• Lead and coordinate cross-functional AI programs from concept to deployment, ensuring alignment with business goals and timelines.
• Partner with data scientists, engineers, and business stakeholders to define and prioritize program objectives.
• Apply statistical analysis and machine learning techniques to address business and operational challenges.
• Translate business requirements into analytical solutions in collaboration with stakeholders.
• Define and translate business needs into actionable AI use cases and technical requirements.
• Build and deploy predictive models to forecast warranty claims, failure rates, and cost trends.
• Ensure data quality, lineage, documentation, and governance compliance.
• Create dashboards and analytical outputs that drive insight adoption and measurable operational impact.
• Collaborate with business data engineers and platform teams on scalability, performance, and best practices.

Requirements

• Bachelor's degree in Data Science, Statistics, Engineering, Computer Science, or a related field.
• Minimum of 3 years' experience as a Data Scientist, Advanced Analyst, or similar role.
• Strong proficiency in Python, SQL, PySpark, and visualization tools such as Power BI or Foundry Workshop.
• Solid foundation in statistics, exploratory data analysis, and applied machine learning.
• Experience handling large, complex datasets in enterprise environments.
• Ability to communicate analytical findings clearly to both technical and non-technical audiences.
• Proven track record delivering end-to-end analytics or data science solutions into production.
• Experience with one or two data and cloud platforms (examples include Palantir Foundry, Snowflake, Databricks on AWS, Azure, or GCP).
• Strong communication and stakeholder engagement skills.

Technologies

• Python
• SQL
• PySpark
• Power BI
• Foundry Workshop
• AWS
• Azure
• DB2
• Palantir Foundry
• Snowflake
• Databricks
• GCP

Preferred Qualifications

• Familiarity with data modeling, semantic layers, and enterprise data platforms.
• Industry experience in automotive and manufacturing.
• Exposure to MLOps concepts, model deployment, or monitoring.
• Hands-on experience with Palantir Foundry and Snowflake Intelligence.
• Master's degree in Data Science, Statistics, Engineering, Computer Science, or a related field.
• Fast-paced, collaborative environment that emphasizes speed and quality to drive measurable business value.