Lead Data Architect

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.  

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 McLaren, Aviva, Deloitte, Spotify, Disney, ING, UPS, Tesco, Truecaller, AllSaints, Volotea, Schmitz Cargobull, Allegro, InPost, 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:

 

• leading the design, governance, and evolution of the enterprise-wide Data & AI architecture,
• driving the Data & AI Design Authority by reviewing solution designs, defining architectural standards, and managing governance and escalation processes,
• establishing and maintaining Data, AI, and Integration architecture blueprints, best practices, and technology standards,
• guiding and developing the Data & AI Center of Excellence (CoE), ensuring alignment between technical initiatives and business strategy,
• defining and consolidating global Data & AI services in collaboration with Operations, including SLAs, governance models, and stakeholder responsibilities,
• owning the architecture and strategic development of the Kafka-based integration platform, including technical standards, partnerships, and support models,
• partnering with Business Units, Platforms, and IT teams to drive the adoption of enterprise Data & AI standards and operating models,
• designing scalable multi-region and multi-cloud data architectures, addressing data gravity, replication, performance, and resilience challenges,
• leveraging Databricks and Kafka to build modern, scalable data solutions while ensuring strong data governance and architectural consistency,
• acting as a trusted advisor to senior business and technology stakeholders, translating complex technical concepts into business value.

 

Your profile:

 

• proven experience as a Lead, Principal, or Enterprise Data Architect in large-scale, international organizations,
• strong hands-on expertise with modern data platforms, particularly Databricks for data storage and processing,
• extensive experience with event-driven architecture and streaming technologies, especially Kafka,
• deep understanding of enterprise data architecture, governance frameworks, and architecture review processes,
• experience defining enterprise-wide architecture standards, reference architectures, and technical blueprints,
• strong knowledge of cloud-based data ecosystems, including multi-region and multi-cloud environments,
• excellent stakeholder management skills with the ability to collaborate across business, technology, and operations teams,
• fluent English and French language skills (written and spoken),
• strong communication skills with the ability to translate technical solutions into business outcomes.

Work from the European Union region and a valid work permit are required.

 

Nice to have:

 

• experience establishing or scaling Data & AI Centers of Excellence (CoE),
• knowledge of integration platforms and API-driven architectures,
• experience defining SLAs and operational governance models,
• experience working with globally distributed teams across multiple continents,
• understanding of data compliance and regulatory requirements in international environments,
• background in financial services, payments, or other large-scale digital organizations,
• experience with AI/ML architecture and deployment pipelines,
• exposure to additional data platforms such as Snowflake, Azure Data Services, or Google Cloud Platform,
• experience supporting organizational change initiatives related to data transformation,
• cloud or Data Architecture certifications (AWS, Azure, GCP, or equivalent).

Recruitment Process:

CV review – HR call – Interview – Client Interview – Decision