PrincipalDataArchitect

## Accountabilities Own and define enterprise data architecture strategy across conceptual, logical, and physical layers, ensuring scalable design across business domains such as finance, sales, product, and operations. Design and standardize modern data models and architecture patterns (dimensional, data vault, 3NF, lakehouse) to support analytics, BI, and operational workloads. Lead architecture for cloud data platforms (Snowflake, Databricks, Azure), ensuring optimal performance, scalability, cost efficiency, and reliability. Define and govern end-to-end data pipelines, including ingestion, transformation, integration, and serving layers across batch and real-time systems. Establish enterprise standards for data governance, metadata, lineage, security, and quality in collaboration with governance and compliance teams. Architect AI/ML-ready data ecosystems, including semantic layers, feature stores, RAG patterns, and governed data access for intelligent applications. Provide technical leadership across initiatives, guiding engineering teams from design to implementation and ensuring alignment with enterprise architecture principles. Act as a design authority in architecture reviews, ensuring consistency, scalability, and adherence to best practices across all data solutions. Requirements: Bring 10+ years of experience in data engineering, analytics, or related technical fields, with at least 5+ years in data architecture or solution architecture roles. Demonstrated expertise in designing and scaling enterprise-grade data platforms in cloud environments. Strong hands-on experience with modern data platforms such as Snowflake, Databricks, and Azure data services (Data Lake, Synapse, Azure SQL). Deep knowledge of data modeling approaches including dimensional modeling, normalized schemas, and data vault methodologies. Proven experience with ETL/ELT tools and frameworks such as dbt, Spark, or Azure Data Factory, along with CI/CD practices. Strong understanding of data