Senior Data Solutions Architect (AWS, Big Data, Data Engineering)

Stellantis • Auburn Hills, MI

12h

About The Position

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. 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.

Requirements

• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related technical discipline.
• 5+ years of experience in data engineering, software development, or data platform architecture.
• 4+ years of hands-on experience building and maintaining production-grade data applications.
• 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.

Nice To Haves

• 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

Responsibilities

• 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.
• 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.
• 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.
• 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.
• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior