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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