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Mid-level QA title but niche ETL/BI and insurance domain requirements limit broad applicant competition.
Strong ETL/BI skills transfer across industries, but insurance domain knowledge makes fit moderately specific.
Explicit years plus mandatory SQL, ETL/BI automation and insurance domain skills make filters stringent.
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Lead ETL workflow testing and data validation across multiple layers including ingestion, staging, transformation, and loading to ensure data integrity in insurance datasets.
Validate BI dashboards and reports for metric accuracy, data consistency, and alignment with business rules, collaborating with cross-functional teams.
Develop and execute complex SQL queries, test plans, and automation scripts while tracking QA metrics such as defect rates and test coverage in Agile and CI/CD environments.
4-6+ years of experience in software quality assurance or quality engineering, specifically in data warehouse testing and data migration validation.
Strong SQL skills including joins, window functions, aggregations, subqueries, and stored procedures.
Experience with automation tools for data validation (e.g., Selenium, QuerySurge, Datagaps, ACCELQ) and Agile/Scrum environments.
Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or related field (or equivalent experience).
Specialist in insurance domain data sets like policy, commissions, premiums, claims, and billing with practical experience in data quality frameworks, metadata management, and MDM.
Proven ability to work hands-on with complex BI tools (Power BI, Tableau) and cloud data warehouses (Snowflake, Azure Synapse, BigQuery).
Experienced in Agile and DevOps/CI-CD environments, capable of driving continuous improvement and cross-team collaboration in testing processes.