Stellantis

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

Stellantis$120K — $150K *
Enterprise Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in Computer Science, Engineering, Mathematics, or related field
  • 5+ years in data engineering, software development, or architecture
  • 4+ years building and maintaining production-grade data applications
  • 4+ years working with AWS cloud services in production
  • Experience designing enterprise-scale data solutions

Responsibilities

  • Lead architecture and design of enterprise data solutions
  • Design secure, scalable, and high-performance data services
  • Define architecture standards and engineering best practices
  • Build scalable data pipelines for connected vehicle data
  • Provide technical direction across multiple teams
  • Establish data quality standards and monitoring frameworks
  • Partner with cross-functional teams to deliver effective solutions

Benefits

  • Comprehensive health and wellness programs
  • Retirement savings plan with company match
  • Opportunities for professional development and growth
  • Flexible work arrangements including remote options
  • Collaborative and innovative work environment
Full Job Description
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.


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

About Stellantis

Stellantis is a multinational automotive manufacturer formed in 2021 by the merger of Fiat Chrysler Automobiles and Groupe PSA. The company designs, produces, and sells a wide range of vehicles under various brands, including Alfa Romeo, Chrysler, Citroen, Dodge, DS Automobiles, Fiat, Jeep, Lancia, Maserati, Opel, Peugeot, Ram, and Vauxhall. Stellantis operates in over 130 countries and has 14 brands in its portfolio. The company is committed to sustainable mobility and has set ambitious targets for reducing its carbon footprint and increasing the share of electric vehicles in its sales.
Learn more about Stellantis
Size
400,000 employees
Market Cap
$44.9 billion
Industry

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