Data AI 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 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:

Design domain data models for parties, deals, assets and payment plans.

Incorporate auditability and historical data requirements into the data model.

Design event streams and integration patterns using outbox, CDC, Kafka and schema registry.

Design the analytics and reporting layer for Risk, Finance and Sales.

Establish metric definitions and support reconciliation and data lineage.

Design governed data context for AI agents, including knowledge graphs, vector stores and masked datasets.

Define data governance approaches for data quality, retention and access control.

Ensure the data architecture addresses GDPR requirements.

Collaborate across Foundation and Lab to align experimental capabilities with the target production architecture.

Your profile:

Strong experience in data architecture and data modelling.

Experience designing domain data models for transactional systems, including auditability and historical records.

Experience with event driven data integration patterns, including outbox and Change Data Capture (CDC).

Experience with Apache Kafka or comparable event streaming architectures.

Understanding of schema management and schema registry concepts.

Experience designing analytics and reporting data architectures.

Understanding of metric definitions, reconciliation and data lineage.

Strong knowledge of data governance, including data quality, retention and access control.

Knowledge of GDPR requirements relevant to data architecture.

Ability to design architectures that support transactional workloads alongside downstream analytics and AI use cases.

Ability to collaborate across prototype and production oriented engineering streams.

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

Nice to have:

Experience designing data architectures for AI or agent based platforms.

Experience with knowledge graphs, vector stores or data prepared for retrieval based AI solutions.

Experience designing approaches for masked or privacy sensitive datasets.

Experience supporting data requirements for Risk, Finance or Sales.

Data architecture experience in financial services, leasing or vendor finance.

Familiarity with data requirements for deterministic core banking systems.

Recruitment Process:

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