Database QA Analyst

As a Data Validation Specialist, you will be responsible for ensuring the accuracy and integrity of data within Snowflake, particularly in the presentation/reporting layer hosted in AWS. Your key responsibilities will include: - Validating data in Snowflake using your expertise in Snowflake data validation techniques. - Building reusable QA/testing frameworks to set up a Snowflake testing framework that allows for the reuse of validation rules across multiple tables, reports, or datasets. - Utilizing Python and Pandas automation to automate validation checks, compare datasets, and streamline manual QA processes. - Leveraging metadata/rules-based testing by defining validation rules in Excel, YAML, or similar metadata files that can be used by a Python test engine to execute tests in Snowflake and generate reports, logs, and alerts. - Demonstrating strong SQL skills for source-to-target testing, including performing row-level validation and writing queries to compare source data with target tables/views to identify discrepancies, gaps, duplicates, or transformation issues. Qualifications required for this role include: - Hands-on experience in Snowflake data validation with a focus on data validation in a presentation/reporting layer hosted in AWS. - Proven track record of building reusable QA/testing frameworks for Snowflake environments. - Proficiency in Python and Pandas for automation of validation checks and comparison of datasets. - Experience in metadata/rules-based testing using Excel, YAML, or similar files to define validation rules. - Strong SQL skills with expertise in source-to-target testing and identifying data discrepancies. The company is also looking for candidates with experience in API-based data validation and testing, which would be considered a plus for this role. As a Data Validation Specialist, you will be responsible for ensuring the accuracy and integrity of data within Snowflake, particularly in the presentation/reporting layer hosted in AWS. Your key responsibilities will include: - Validating data in Snowflake using your expertise in Snowflake data validation techniques. - Building reusable QA/testing frameworks to set up a Snowflake testing framework that allows for the reuse of validation rules across multiple tables, reports, or datasets. - Utilizing Python and Pandas automation to automate validation checks, compare datasets, and streamline manual QA processes. - Leveraging metadata/rules-based testing by defining validation rules in Excel, YAML, or similar metadata files that can be used by a Python test engine to execute tests in Snowflake and generate reports, logs, and alerts. - Demonstrating strong SQL skills for source-to-target testing, including performing row-level validation and writing queries to compare source data with target tables/views to identify discrepancies, gaps, duplicates, or transformation issues. Qualifications required for this role include: - Hands-on experience in Snowflake data validation with a focus on data validation in a presentation/reporting layer hosted in AWS. - Proven track record of building reusable QA/testing frameworks for Snowflake environments. - Proficiency in Python and Pandas for automation of validation checks and comparison of datasets. - Experience in metadata/rules-based testing using Excel, YAML, or similar files to define validation rules. - Strong SQL skills with expertise in source-to-target testing and identifying data discrepancies. The company is also looking for candidates with experience in API-based data validation and testing, which would be considered a plus for this role.