Principal Data Architect

About the role

Description from the employer’s posting. Check the employer’s page for the current version.

Xebia is a global AI-first, digital transformation, and engineering partner. With over 25 years of experience and a team of 5,000 professionals across 16 countries, we help organizations design and build scalable products, platforms, and data-driven solutions. We specialize in Artificial Intelligence, Data and Cloud, Intelligent Automation, and Digital Products, combining deep technical expertise with a strong focus on engineering excellence and a people-first culture. I In the CEE region, we’re a team of nearly 1,000 experts delivering modern applications, data platforms, and AI solutions for clients such as Millennium, ING, Play, Edenred, Arabian Drilling, FedEx, Leroy Merlin, Truecaller, Volotea, Schmitz Cargobull, and many, many more. We work with leading technologies including AWS, Azure, GCP, Databricks, and Snowflake, and combine strong engineering culture with a consulting mindset and a continuous focus on growth and knowledge sharing. You will be: working directly with new clients from discovery through solution shaping: running workshops, exploring requirements, and presenting the proposed solution, technologies, and architecture, supporting the presales team with architect-level input for proposals, turning business and technical expectations into a high-level architecture proposal, including risks, dependencies, and constraints, thinking beyond the single project, shaping our offering and turning the things we build over and over for clients into reusable patterns and accelerators. building the prototype while designing the final product, being the person the project team turns to on the hardest problems, Your profile: solid, current hands-on experience as a Data Architect or Solution Architect, coming from a recent delivery and engineering role. We want someone who still builds, not a theorist, strong hands-on knowledge of at least one major cloud provider (Azure, AWS, or GCP) and modern data platforms such as Databricks or Snowflake, practical experience with lakehouse architecture (Delta Lake or Iceberg, medallion layering) covering both batch and streaming workloads, including real-time architectures, hands-on experience with data platform migration and modernization, and with designing integrations between business systems and data platforms, practical grasp of agentic data engineering, meaning how to build and maintain data pipelines with AI coding agents like Claude Code or Codex, practical understanding of AI/ML and GenAI concepts and how they fit into modern data platform architectures (LLM-based solutions, RAG, MLOps, AI-ready data pipelines), experience producing architecture proposals, solution concepts, and high-level design artifacts, and assessing technical risks and delivery assumptions, strong communication and presentation skills for both technical and non-technical audiences. Work from the European Union region and a work permit are required. Nice to have: technical leadership experience: leading project teams and setting technical direction, experience with governance, security, and data quality, familiarity with enterprise-scale data services beyond a single platform (the broader Azure, AWS, or GCP data ecosystem), hands-on experience building AI-powered solutions (GenAI applications, recommendation systems, intelligent automation), experience supporting RFP, bid, or proposal work, cloud or data platform certifications (Azure, AWS, GCP, Databricks, Snowflake, and similar). Recruitment Process: CV review – HR call – Technical Interview – Client Interview – Decision