• Data Warehousing concepts, data modeling, metadata management • Data lakes, multi-dimensional models, data dictionaries • Migration to AWS or Azure Snowflake platform • Performance tuning and setting up resource monitors • Snowflake modeling – roles, databases, schemas • SQL performance measuring, query tuning, and database tuning • ETL Tools with cloud-driven skills • Integration with third-party tools • Ability to build analytical solutions and models • Coding in languages like Python, Java, • Root cause analysis of models with solutions • Hadoop, Spark, and other warehousing tools • Managing sets of XML, JSON, and CSV from disparate sources • SQL-based databases like Oracle SQL Server, Teradata, etc. • Snowflake warehousing, architecture, processing, administration • Data ingestion into Snowflake • Enterprise-level technical exposure to Snowflake applications