We are looking for a talented and experienced Data Architect to join our Budapest-based team. The successful candidate will play a central role in shaping our data landscape across multiple value streams. The role requires deep expertise in data integration, data modelling, and analytical engineering. You will collaborate closely with product, engineering, and analytics teams to design and govern data architectures that power key business capabilities.    Key Responsibilities Data Architecture & Modelling Design and maintain enterprise-wide data models, including conceptual, logical, and physical layers Lead data architecture for core platforms and support cross-value-stream data requirements Define data standards, naming conventions, and modelling best practices Evaluate and recommend appropriate data storage patterns (relational, dimensional, lakehouse, graph) Data Integration Architect and oversee data pipelines and ETL/ELT processes across source systems Design integration patterns for batch, near-real-time, and streaming data flows Ensure robust data lineage, traceability, and auditability across all pipelines Collaborate with engineering teams to implement scalable, resilient integration solutions Analytics Enablement Develop semantic and analytical data models that serve BI, reporting, and advanced analytics use cases Partner with analytics and data science teams to define trusted data products Champion a self-service data culture by enabling reusable, well-documented data assets Governance & Quality Define and enforce data quality rules, validation frameworks, and remediation processes Contribute to data governance policies, data cataloguing, and metadata management Work with stakeholders to manage data contracts and SLAs Stakeholder Collaboration Act as a trusted data advisor across multiple value streams and business units Facilitate technical workshops and design reviews with engineering and product stakeholders Communicate complex data architecture decisions clearly to both technical and non-technical audiences