Build the Future of Connected Vehicle Data at Stellantis
Stellantis is transforming the future of mobility through connected vehicles, advanced
analytics, artificial intelligence, and data-driven products. Our AI & Data Analytics team
develops scalable platforms and innovative data solutions that power some of the world's
most recognized automotive brands.
We are seeking a Senior Data Solutions Architect to lead the design and implementation of
enterprise-scale data products and platforms. This role combines technical leadership,
architecture, cloud engineering, and stakeholder collaboration to deliver secure, scalable,
and high-performance data solutions that support both internal software products and
external customer offerings.
If you are passionate about cloud architecture, big data technologies, real-time data
processing, and building modern data platforms from the ground up, we'd like to hear from
you.
About the Role
As a Senior Data Solutions Architect, you will serve as a technical leader responsible for
defining architecture, driving technology decisions, and building scalable data services
that support Stellantis' connected vehicle ecosystem.
You will be a partner with engineering, product, analytics, and business teams to develop
modern cloud-based data platforms, establish engineering best practices, and ensure
data quality across the organization.
This role requires expertise in data architecture, cloud technologies, and distributed
processing systems, real-time data pipelines, and large-scale data engineering.
What You'll Do
Data Architecture & Solution Design
- Lead the architecture and technical design of enterprise data solutions for internal
- platforms and customer-facing products.
- Design and implement secure, scalable, resilient, and high-performance data
- services using modern cloud and Big Data technologies.
- Define architecture standards and engineering best practices for data platforms
- and analytics solutions.
- Evaluate technology options and make architecture decisions that align with
- business and technical objectives.
Cloud & Big Data Engineering
- Design and implement distributed data processing solutions using cloud-native
- technologies.
- Build scalable data pipelines for ingestion, transformation, validation, and delivery
- of connected vehicle data.
- Develop real-time and batch processing architectures that support growing
- business needs.
- Ensure data platforms meet performance, reliability, scalability, and security
- requirements.
Technical Leadership
- Provide technical direction across multiple engineering teams.
- Influence architectural decisions and drive alignment across cross-functional organizations.
- Lead implementation efforts from concept through production deployment.
- Mentor and support engineers and technical team members to help grow organizational capabilities.
Data Quality & Operational Excellence
- Establish and maintain data quality standards, validation processes, and
- monitoring frameworks.
- Lead efforts to standardize instrumentation, observability, and operational
- readiness across software platforms.
- Develop comprehensive documentation, runbooks, and troubleshooting
- processes.
- Drive continuous improvement initiatives across data engineering and platform operations.
Stakeholder Collaboration
- Partner with product, engineering, analytics, and business teams to understand
- complex requirements and deliver effective solutions.
- Build strong relationships with upstream and downstream stakeholders to ensure
- successful delivery of data products.
- Translate technical concepts into clear business outcomes and recommendations.
*
Basic Qualifications:*
- Bachelor's degree in Computer Science, Engineering, Mathematics, or a related technical discipline.
- A minimum of 8 years of experience in data engineering, software development, or data platform architecture. Including:
- A minimum of 4 years of hands-on experience building and maintaining production-grade data applications.
- A minimum of 4 years of experience working with AWS cloud services in production environments.
- Experience designing and implementing enterprise-scale data solutions and platforms.
- Data architecture and data modeling
- Relational and columnar database technologies
- Operational data stores
- Master data management
- ETL and ELT design, implementation, and optimization
- Data quality management and validation frameworks
- AWS cloud services
- Apache Spark
- Distributed data processing platforms
- Python
- Java
- Notification Event Bus
- Kinesis
- SNS (Simply Notification Service)
- SQS (Simple Queue Service)
- MQ (Message Queue)
- Apache Airflow
- Azure Data Factory
- Workflow orchestration platforms
- API design and development
- Data service architecture
- Integration patterns and distributed systems
- Experience leading cross-functional technical initiatives.
- Ability to architect solutions from concept through implementation.
- Strong communication skills with the ability to translate complex technical concepts into business-focused solutions.
- Experience mentoring and guiding engineering teams.
Preferred Qualifications:
- AWS certification or equivalent cloud certification.
- Experience with Databricks and Databricks notebook workflows.
- Experience with Infrastructure as Code (IaC) tools such as Terraform.
- Experience supporting enterprise analytics, machine learning, or AI-driven platforms.
- Experience working with connected vehicle, IoT, or large-scale telemetry data
