Xebia is a global AI-first digital transformation and engineering partner. With over 25 years of experience and a large team across multiple countries, we help organizations design and build scalable products, platforms, and data-driven solutions. You will analyze and assess current multi-store reporting architectures, design scalable, high-performance reporting solutions capable of handling very large data volumes, define data modeling strategies for analytics and reporting workloads, design approaches for event enrichment using metadata from multiple sources, create efficient solutions for computing unique counts and analytical aggregations at scale, and provide architectural guidance around real-time and near real-time analytics. You will evaluate and recommend technologies, patterns, and trade-offs across the data platform, collaborate with engineering teams to implement the proposed architecture, support migration activities and ensure reporting consistency throughout the transition, and drive best practices related to data quality, scalability, observability, and performance optimization. You will provide technical guidance and mentorship to engineering team members. Your profile: 7+ years of experience in Data Engineering, Data Architecture, or related roles, strong hands-on experience with Apache Druid, strong experience with Kafka and event-driven architectures, excellent knowledge of large-scale analytical data modeling, experience designing real-time or near real-time reporting platforms, strong expertise in SQL and MySQL, experience processing and analyzing bill

Xebia is a global AI-first digital transformation and engineering partner. With over 25 years of experience and a large team across multiple countries, we help organizations design and build scalable products, platforms, and data-driven solutions. You will analyze and assess current multi-store reporting architectures, design scalable, high-performance reporting solutions capable of handling very large data volumes, define data modeling strategies for analytics and reporting workloads, design approaches for event enrichment using metadata from multiple sources, create efficient solutions for computing unique counts and analytical aggregations at scale, and provide architectural guidance around real-time and near real-time analytics. You will evaluate and recommend technologies, patterns, and trade-offs across the data platform, collaborate with engineering teams to implement the proposed architecture, support migration activities and ensure reporting consistency throughout the transition, and drive best practices related to data quality, scalability, observability, and performance optimization. You will provide technical guidance and mentorship to engineering team members. Your profile: 7+ years of experience in Data Engineering, Data Architecture, or related roles, strong hands-on experience with Apache Druid, strong experience with Kafka and event-driven architectures, excellent knowledge of large-scale analytical data modeling, experience designing real-time or near real-time reporting platforms, strong expertise in SQL and MySQL, experience processing and analyzing bill