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Must haves: Snowflake data validation experience must be able to validate data in Snowflake, especially in a presentation/reporting layer hosted in AWS. Experience building reusable QA/testing frameworks must have experience setting up a Snowflake testing framework where validation rules can be reused across multiple tables, reports, or datasets. Python and Pandas automation experience must be able to use Python scripts and Pandas to automate validation checks, compare datasets, and reduce manual QA effort. Metadata/rules-based testing experience must understand how to use Excel, YAML, or similar metadata files to define validation rules that feed into a Python test engine, execute in Snowflake, and produce reports/logs/alerts. Strong SQL skills for source-to-target testing must have row level validation expertise and be comfortable writing queries to compare source data to target tables/views and identify mismatches, gaps, duplicates, or transformation issues. Plusses: API based data validation and testing .