Role intent:
A hands-on individual contributor role focused on building and maintaining reliable data pipelines, curated datasets, and governed analytics-ready data products.
Position Summary:
The Customer Data Platform team is seeking a Data Engineer to help build and maintain trusted data products that power marketing performance, customer analytics, and advanced decisioning.
This role will work closely with data scientists, analysts, and business stakeholders to develop scalable data pipelines, support analytics initiatives, and ensure the availability of high-quality data across the organization.
The ideal candidate is a hands-on data engineering professional with strong technical skills, a passion for data quality, and experience developing data solutions in a modern cloud environment.
Key Responsibilities:
Data Engineering & Pipeline Development:
- Design, build, and maintain secure, scalable data pipelines that support reporting, analytics, and machine learning initiatives
- Develop and optimize ETL/ELT processes to ingest, transform, and deliver data from multiple sources
- Support data integration efforts across customer, marketing, digital, and enterprise data domains
- Implement data quality checks, validation processes, and monitoring solutions to ensure trusted data products
- Troubleshoot and resolve data pipeline and data quality issues in production environments
Data Modeling & Analytics Enablement:
- Build and maintain scalable data models that support analytics and reporting requirements
- Develop curated datasets that enable consistent business metrics and KPI reporting
- Collaborate with analysts and data scientists to support advanced analytics, audience development, customer insights, and performance measurement
- Assist in implementing data structures that improve usability, consistency, and reusability across teams
Collaboration & Delivery:
- Partner with business stakeholders to understand requirements and translate them into technical solutions
- Work closely with cross-functional teams to deliver reliable and scalable data products
- Participate in code reviews, testing, deployment activities, and continuous improvement initiatives
- Contribute to documentation, knowledge sharing, and engineering best practices
Data Governance & Reliability:
- Follow established standards for data governance, security, privacy, and compliance
- Monitor pipeline performance and recommend opportunities for optimization
- Support efforts to improve data quality, reliability, and operational efficiency
- Maintain documentation for data pipelines, data models, and technical processes
Basic Qualifications:
- Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, or a related field
- 8 years of experience in data engineering
- Strong SQL development skills
- Experience developing and supporting ETL/ELT pipelines
- Experience working with cloud-based data platforms and modern data architectures (e.g., Azure, Snowflake, BigQuery, AWS)
- Proficiency in Python, Spark, or similar data processing technologies
- Experience working with structured and semi-structured data
- Understanding of data modeling concepts, including dimensional modeling and data warehousing principles
- Strong analytical and problem-solving skills
- Ability to collaborate effectively with both technical and business stakeholders
Preferred Qualifications:
- Experience supporting marketing, customer, digital, or analytics use cases
- Experience with orchestration and workflow automation tools
- Familiarity with customer data platforms, customer analytics, or audience management solutions
- Experience with machine learning data preparation and feature engineering
- Understanding of data governance and data quality best practices
Skills Required
- Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, or a related field
- 8 years of experience in data engineering
- Strong SQL development skills
- Experience developing and supporting ETL/ELT pipelines
- Experience with cloud-based data platforms and modern data architectures, such as Azure, Snowflake, BigQuery, or AWS
- Proficiency in Python, Spark, or similar data processing technologies
- Experience working with structured and semi-structured data
- Understanding of data modeling concepts, including dimensional modeling and data warehousing principles
- Strong analytical and problem-solving skills
- Ability to collaborate effectively with technical and business stakeholders
- Experience supporting marketing, customer, digital, or analytics use cases
- Experience with orchestration and workflow automation tools
- Familiarity with customer data platforms, customer analytics, or audience management solutions
- Experience with machine learning data preparation and feature engineering
- Understanding of data governance and data quality best practices
Stellantis Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Stellantis and has not been reviewed or approved by Stellantis.
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Pay Growth & Progression — Contract-driven increases lifted hourly wages roughly 25% over 4.5 years and restored cost-of-living adjustments, pushing top rates near $42 per hour by the end of the agreement. Union hourly positions appear to have benefited most since the 2023 deal.
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Affordable Benefits — UAW-represented hourly workers pay no premiums and about 3% of total healthcare costs while receiving comprehensive medical, dental, vision, and wellness coverage. This creates materially lower out-of-pocket costs for represented hourly roles.
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Retirement Support — Post-2007 hourly hires receive a 10% employer 401(k) contribution and legacy workers saw defined-benefit improvements with retiree bonuses. Salaried roles also cite a 401(k) with employer match and contribution up to a maximum of 8%.
Stellantis Insights
What We Do
Our storied and iconic brands embody the passion of their visionary founders and today’s customers in their innovative products and services: they include Abarth, Alfa Romeo, Chrysler, Citroën, Dodge, DS Automobiles, Fiat, Jeep®, Lancia, Maserati, Opel, Peugeot, Ram, Vauxhall and mobility brands Free2move and Leasys. Powered by our diversity, we lead the way the world moves – aspiring to become the greatest sustainable mobility tech company, not the biggest, while creating added value for all stakeholders as well as the communities in which we operate.
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