[Hiring] Data AI Architect @Poland and Central-Eastern Europe

Role Description

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.

Qualifications

• 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.

Requirements

• 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