Design and implement Snowflake schemas, tables, views, materialized views, and stages to support migrated workloads. Recreate/translate Yellowbricks tables, views, and logic into Snowflake with functional equivalence. Collaborate with dbt developers to ensure dbt models are aligned with Snowflake best practices (clustering, micro-partitioning, warehouses). Develop and optimize SQL scripts, stored procedures (Snowflake Scripting), and views used by dbt, Databricks, and BI tools. Implement and manage Snowflake roles, grants, and security models in line with enterprise standards. Support performance tuning for complex queries, including warehouse sizing, result caching, clustering, and statistics. Assist with data migration and validation between Yellowbricks and Snowflake (row counts, aggregates, and spot checks). Contribute to CI/CD implementation for Snowflake objects (using Azure DevOps or similar). Work closely with onshore architects and leads, attending overlap meetings in US time zones as required. 2-4 years of experience in Data Engineering / DW development, with 2+ years on Snowflake. Strong hands-on SQL skills and experience with large-scale DW solutions. Solid understanding of Snowflake architecture (warehouses, databases, schemas, stages, virtual warehouses, security roles). Experience with cloud platforms, ideally Azure and its integration with Snowflake (ADLS/Blob, ADF/Synapse, Key Vault). Prior exposure to migration from MPP platforms (Yellowbricks, Teradata, Netezza, etc.) to Snowflake is a plus. Familiarity with dbt, Databricks, or ETL tools (Informatica) is an advantage. Experience working in offshore delivery models, collaborating with onshore teams.
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