Senior QA Engineer

Introduction Welcome to Gallagher in India — where expertise, technology, and purpose come together. Since 2006, Gallagher in India has supported global teams by delivering quality, service, and speed through deep expertise, smart technology, and specialized knowledge services. More than just an operations center, it’s a place where careers grow through collaboration, continuous learning, and purposeful work. We drive efficiency, compliance, and innovation so our teams can focus on serving clients. If you enjoy solving problems and working with purpose, Gallagher is the place where you can grow and feel a sense of belonging. Overview Position Summary: ETL DATA Tester (Manual) We are seeking a highly skilled QA Tester with deep experience in data warehouse testing, ETL validation, and BI reporting within the insurance industry. The ideal candidate will have strong analytical abilities, excellent SQL skills, and a proven track record of ensuring data integrity, accuracy, and completeness across complex data ecosystems. This role involves collaborating in cross-functional teams, contributing to the testing maturity, and driving continuous improvement in the testing process. They will be hands-on with test planning, execution, and automation, working closely with other testers in their area, both internal and third party, to cover a range of test types both functional and non-functional. Thorough understanding of SDLC and QA processes in an Agile delivery environment. Self-motivated in handling multiple assignments across cross-functional teams. How you'll make an impact Responsibilities: •Perform detailed ETL workflow testing across ingestion, staging, transformation, and loading layers. •Validate complex business rules, mappings, and transformation logic. •Test data across star schema, snowflake, fact, and dimension tables. •Validate end-to-end data migration from legacy to new systems or cloud platforms. •Conduct record counts, data reconciliation, field-to-field mapping validation, and defect analysis. •Ensure no data loss, duplication, or corruption during migration. •Test BI dashboards and reports (Power BI, Tableau, Qlik, Cognos, etc.) for metric accuracy and data consistency. •Validate report filters, drill-downs, KPIs, aggregations, and business definitions. •Cross-verify displayed data with source databases, staging layers, and DWH. •Collaborate with Product Owner, data engineers, Tech leads, and business SMEs to ensure alignment with requirements. •Write and execute complex SQL queries for comprehensive data validation. •Create test plans, test cases, mapping sheets, data validation scripts, and defect logs. •Support Agile/Scrum processes and CI/CD testing workflows. •Identify, document, and track data quality issues through resolution. •Track and report meaningful QA metrics such as defect rates, test coverage, and automation effectiveness. •Stay current with industry trends, emerging tools, and QA best practices. About you Qualifications: •Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or related field (or equivalent experience). Experience Required: •4-6+ years of experience in software quality assurance or quality engineering. •Practical experience with automation tools (e.g., Selenium, Query Surge, Datagaps, ACCELQ). •Experience working within Agile/Scrum environments. Technical Skills: •Strong SQL skills (joins, window functions, aggregations, subqueries, store procedure). •Experience with automation tools for data validation such as Datagaps, QuerySurge, AccelQ, Selenium etc. •Experience with data migration testing (legacy to modern systems or cloud). •Strong understanding of insurance domain datasets—policy, commissions, premiums, claims, billing etc. •Exposure to data quality frameworks, metadata management, and MDM principles. •Experience testing pipelines in DevOps/CI-CD environments. •Experience validating BI reports (Power BI, Tableau). •Familiarity with cloud DWH platforms (Snowflake, Azure Synapse, BigQuery). •Experience with performance testing (e.g., JMeter) is a plus. •Knowledge of ETL/ELT transformation and workflow automation tools such as DBT, Dataiku, and Astronomer. Soft Skills: •Strong leadership abilities and a collaborative mindset. •Excellent problem-solving and analytical skills. •Clear communication skills, both written and verbal. •Ability to work effectively with cross-functional teams. Preferred Qualifications: •QA or testing certifications (ISTQB, CSTE, CSQE, etc.). •Experience with AI/ML-based testing tools. •Understanding of compliance standards (SOC 2, ISO 27001, etc.). Additional Information At Gallagher, we believe supporting our colleagues goes far beyond the role itself. For more information, visit our Benefits page. Competitive compensation Comprehensive benefits programs designed to support your well-being Career development opportunities and ongoing learning A collaborative, people-first culture with accessible leadership The opportunity to do meaningful work with global reach and local impact At Gallagher, we are dedicated to building an inclusive and authentic workplace. If your past experience doesn’t align perfectly, we encourage you to join our Talent Community to stay connected to additional career opportunities. At times, we will consider transferable skills from previous roles. Gallagher is an affirmative action/equal opportunity employer (Minorities/Females/Veterans/Disabled) Responsibilities: •Perform detailed ETL workflow testing across ingestion, staging, transformation, and loading layers. •Validate complex business rules, mappings, and transformation logic. •Test data across star schema, snowflake, fact, and dimension tables. •Validate end-to-end data migration from legacy to new systems or cloud platforms. •Conduct record counts, data reconciliation, field-to-field mapping validation, and defect analysis. •Ensure no data loss, duplication, or corruption during migration. •Test BI dashboards and reports (Power BI, Tableau, Qlik, Cognos, etc.) for metric accuracy and data consistency. •Validate report filters, drill-downs, KPIs, aggregations, and business definitions. •Cross-verify displayed data with source databases, staging layers, and DWH. •Collaborate with Product Owner, data engineers, Tech leads, and business SMEs to ensure alignment with requirements. •Write and execute complex SQL queries for comprehensive data validation. •Create test plans, test cases, mapping sheets, data validation scripts, and defect logs. •Support Agile/Scrum processes and CI/CD testing workflows. •Identify, document, and track data quality issues through resolution. •Track and report meaningful QA metrics such as defect rates, test coverage, and automation effectiveness. •Stay current with industry trends, emerging tools, and QA best practices. Qualifications: •Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or related field (or equivalent experience). Experience Required: •4-6+ years of experience in software quality assurance or quality engineering. •Practical experience with automation tools (e.g., Selenium, Query Surge, Datagaps, ACCELQ). •Experience working within Agile/Scrum environments. Technical Skills: •Strong SQL skills (joins, window functions, aggregations, subqueries, store procedure). •Experience with automation tools for data validation such as Datagaps, QuerySurge, AccelQ, Selenium etc. •Experience with data migration testing (legacy to modern systems or cloud). •Strong understanding of insurance domain datasets—policy, commissions, premiums, claims, billing etc. •Exposure to data quality frameworks, metadata management, and MDM principles. •Experience testing pipelines in DevOps/CI-CD environments. •Experience validating BI reports (Power BI, Tableau). •Familiarity with cloud DWH platforms (Snowflake, Azure Synapse, BigQuery). •Experience with performance testing (e.g., JMeter) is a plus. •Knowledge of ETL/ELT transformation and workflow automation tools such as DBT, Dataiku, and Astronomer. Soft Skills: •Strong leadership abilities and a collaborative mindset. •Excellent problem-solving and analytical skills. •Clear communication skills, both written and verbal. •Ability to work effectively with cross-functional teams. Preferred Qualifications: •QA or testing certifications (ISTQB, CSTE, CSQE, etc.). •Experience with AI/ML-based testing tools. •Understanding of compliance standards (SOC 2, ISO 27001, etc.).