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Hybrid mid-senior QA with a generalist title but analytics specialization creates medium applicant competition.
Analytics QA with Snowflake and ETL focus is moderately transferable across data-driven industries.
Mandatory 6+ years QA, Snowflake/data warehouse expertise, and advanced SQL enforce strict shortlisting filters.
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Own end-to-end quality assurance for reporting dashboards, data pipelines, and analytics tools, including designing test strategies and validating data accuracy.
Collaborate with data engineers, product managers, and developers to define correctness criteria before feature release.
Conduct various testing types (functional, regression, performance, integration) focused on data accuracy across multiple sources and ETL processes.
6+ years of QA experience with focus on reporting or analytics systems.
Strong SQL skills to write and execute queries on relational databases like Snowflake or equivalent.
Bachelor's degree in Computer Science, Information Systems, or related field.
Experience validating data accuracy across data warehouses, ETL pipelines, and visualization tools.
Experience working closely with cross-functional teams in defining and validating data correctness pre-release in complex data environments.
Strong analytical and detail-oriented operating style focusing on subtle data issues beyond basic functional testing.
Background or familiarity with Agile/Scrum processes, data modeling, and potentially payroll or HRIS domains is a plus but not mandatory.