Snowflake Data engineers

Migrate the Pest database schema and data from the legacy VM/SQL environment into Snowflake while preserving required behaviors and data quality, and will analyze and re-platform Pest-related SSIS packages and stored procedures into Snowflake-native SQL constructs such as views, stored procedures, tasks, streams, and dynamic tables. 

The Project will implement Snowflake ELT layers for Pest, including RAW ingestion layers using Fivetran and modeled, presentation layers aligned with existing Group Data Warehouse ("GDW") and GDW Application patterns.

Another key objective is to implement robust data testing and reconciliation between the legacy SQL environment and Snowflake, covering schemas, volumes, and sampled data quality checks, while establishing basic observability patterns such as logging, audit tables, and integration points for alerting where feasible, and enabling downstream analytics and reporting platforms to consume Pest data from Snowflake with minimal changes beyond connection and data source updates and compatibility views. Schema drift while development and testing will also be accounted for to ensure business continuity during the migration.