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

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.

Requirements:

Required Qualifications

Education

• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related technical discipline.

Experience

• 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.

Technical Skills

Data Architecture & Engineering

• 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

Cloud & Big Data Technologies

• AWS cloud services
• Apache Spark
• Distributed data processing platforms

Programming Languages

• Python
• Java

Streaming & Real-Time Data

• Notification Event Bus
• Kinesis
• SNS (Simply Notification Service)
• SQS (Simple Queue Service)
• MQ (Message Queue)

Data Orchestration & Workflow Management

• Apache Airflow
• Azure Data Factory
• Workflow orchestration platforms

API & Platform Development

• API design and development
• Data service architecture
• Integration patterns and distributed systems

Leadership Skills

• 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