Senior Data Architect

📋 Description

• Define and own the enterprise data architecture strategy across core domains.
• Govern data standards, naming conventions, schema design, and modeling practices.
• Lead scalable data products in semantic/analytical layers for self-service.
• Partner with Product Data to align on standards, data contracts, and platform decisions.
• Evaluate data platforms: warehouses, lakehouses, orchestration, catalogs.
• Identify architectural gaps and data quality risks across the estate.

🎯 Requirements

• 5+ years in data architecture or related discipline.
• Experience governing enterprise data models across transactional, analytical, semantic layers.
• Deep expertise in modern data stacks: Snowflake, BigQuery, Databricks, lakehouse, dbt.
• Strong data modeling: dimensional modeling, Data Vault, OBT.
• Experience leading data governance programs incl. metadata, lineage, quality.
• Able to translate architectural decisions into business value with stakeholders.

🎁 Benefits

• Experience in a company with centralized data functions.
• Familiarity with semantic layer tools (Cube, LookML) and headless BI.
• Background in data mesh, data product, or federated governance.
• Experience with real-time streaming data architectures (Kafka, Flink).