Data Architect – Governance, Quality

• Design semantic, logical, and conceptual data models based on business domains and organizational processes
• Define and standardize the corporate data model as part of the Data Governance initiative
• Create and maintain logical and technical reference architectures and design patterns for data domains
• Co-create the strategy and roadmap for data architecture development
• Collaborate with Data Governance, Data Management, Analytics, AI, and Data Engineering teams to integrate models with data catalog and metadata management tools
• Support technical teams in implementing models in data layers
• Participate in designing data integration, flow, and quality processes, including data lineage, data contracts, and data quality
• Identify and certify authoritative data sources within organizational domains
• Monitor compliance of data solutions with Data Governance policies, standards, and architectural recommendations
• Support resolution of data conflicts and issues
• Create architectural documentation, metamodels, and inter-domain relationship diagrams
• Consult on and develop practices for modeling, metadata, and information architecture
• Collaborate on the vision, priorities, and directions for data architecture development
• Partner with sales and industry teams on technical presales, including discovery workshops, solution design, estimations, and technical proposal and RFP content
• Present architectures and recommendations to client stakeholders from engineering teams to C-level
• Design and run proofs of concept and technical demos
• Evaluate new approaches and tools such as data mesh, streaming-first, and AI-native platforms, and share findings internally and externally

• Experience in Data Governance, Data Quality, Master Data, and Metadata Management projects
• Experience in conceptual, logical, and physical data modeling, preferably in a large organization or within complex data ecosystems
• Deep knowledge of modern Data Platforms, including Snowflake and Databricks
• Practical knowledge of ER, UML, IDEF1X, Data Vault, 3NF, and Kimball/Inmon
• Ability to work with data catalogs and metadata management tools such as DataHub, Collibra, Alation, and Atlan
• Knowledge of SQL and relational data models
• Experience with database systems and data architecture in cloud environments: AWS, GCP, and Azure
• Ability to translate business needs into data models with engineering and analytics teams
• Understanding of data security, availability, and control principles
• Good command of English for reading documentation and community discussions
• Knowledge of semantic data layer concepts and technologies, including ontologies, RDF, OWL, GraphQL, dbt Semantic Layer, and Semantic Kernel
• Knowledge of Python for automation, model validation, and API integrations
• Knowledge of event-driven data architecture
• Experience creating and maintaining architectural documentation

• Flexible and remote cooperation options
• International projects with leading global clients
• Travels related to international projects
• Non-corporate atmosphere
• Access to language classes
• Access to knowledge-sharing initiatives
• Access to private healthcare and life insurance
• Access to multisport card