Snowflake Architect- PAN India
2 weeks ago
Data Architecture experience in Data Warehouse, Snowflake+ DBT
Snowflake + snowflake advanced certification
• Oversees and designs the information architecture for the data warehouse, including all information structures i.e. staging area, data warehouse, data marts, operational data stores, oversees standardization of data definition, Oversees development of Physical and Logical modelling.
• Deep understanding in Data Warehousing, Enterprise Architectures, Dimensional Modelling, Star & Snow-flake schema design, Reference DW Architectures, ETL Architect, ETL (Extract, Transform, Load), Data Analysis, Data Conversion, Transformation, Database Design, Data Warehouse Optimization, Data Mart Development, and Enterprise Data Warehouse Maintenance and Support etc.
• Significant experience in working as a Data Architect with depth in data integration and data architecture for Enterprise Data Warehouse implementations (conceptual, logical, physical & dimensional models).
• Maintain in-depth and current knowledge of the Cloud architecture, Data lake, Data warehouse, BI platform, analytics models platforms and ETL tools
Essential job tasks
Data Architecture experience in Data Warehouse, Snowflake.
• Oversees and designs the information architecture for the data warehouse, including all information structures i.e. staging area, data warehouse, data marts, operational data stores, oversees standardization of data definition, Oversees development of Physical and Logical modelling.
• Deep understanding in Data Warehousing, Enterprise Architectures, Dimensional Modelling, Star & Snow-flake schema design, Reference DW Architectures, ETL Architect, ETL (Extract, Transform, Load), Data Analysis, Data Conversion, Transformation, Database Design, Data Warehouse Optimization, Data Mart Development, and Enterprise Data Warehouse Maintenance and Support etc.
• Significant experience in working as a Data Architect with depth in data integration and data architecture for Enterprise Data Warehouse implementations (conceptual, logical, physical & dimensional models).
• Maintain in-depth and current knowledge of the Cloud architecture, Data lake, Data warehouse, BI platform, analytics models platforms and ETL tools
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