Overview

We are looking for a Senior Data Architect to design and evolve a modern, scalable cloud data platform on AWS with Databricks. This role combines hands-on architecture, data platform design, and cross-functional collaboration. You will be involved in defining data architecture standards, enabling scalable analytics solutions, and supporting data driven decision making across the organization. Client: The world’s largest sporting goods retailer, with a global team of 5,000+ experts across engineering, product, data, cloud, and cybersecurity, is building the largest digital sports platform driving innovation from product design to customer experience and sustainability. Project Overview: The project focuses on building a centralized cloud data platform that supports large scale data ingestion, processing, and analytics workloads. The platform enables advanced reporting, analytics, and data science use cases across multiple domains.

Responsibilities:
  • Design and evolve end-to-end data architecture on cloud platforms
  • Define data models, pipelines, and architectural standards for analytics and reporting
  • Lead architectural decisions for data ingestion, transformation, and storage using Databricks
  • Collaborate with data engineers and platform teams to ensure scalability and reliability
  • Support data governance, security, and compliance frameworks
  • Review implementations and ensure alignment with architectural principles
  • Communicate complex architectural concepts to both technical and non-technical stakeholders
Required Qualifications:
  • Proven experience working as a Data Architect in complex data environments
  • Hands on experience designing data platforms on AWS
  • Practical experience with Databricks and Spark based data processing
  • Strong knowledge of data modeling, data warehousing, and analytics architectures
  • Experience working with large scale data pipelines and cloud native services
  • Strong programming skills (Python, SQL)
  • Professional working proficiency in French
  • Professional working proficiency in English
Nice To Have:
  • Experience with data governance or data quality frameworks
  • Exposure to real time or streaming data architectures
  • Experience working with data science or machine learning teams
  • Background in regulated or enterprise scale environments
Note:

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