Database qa analyst

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