$ cat jobs/senior-staff-engineer-qa-etl-nagarro1-b37fc2bafe48.json
Senior Staff Engineer,QA ETL
👋🏼 We're Nagarro. We are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at scale across all devices and digital mediums, and our people exist everywhere in the world (18500+ experts across 40 countries, to be exact). Our work culture is dynamic and non-hierarchical. We're looking for great new colleagues. That's where you come in! REQUIREMENTS: Total experience: 7.5 – 9 years. Strong experience in ETL Testing and Data Warehouse Testing. Must-have expertise in Advanced SQL. Hands-on experience with Snowflake. Experience testing MongoDB data sources. Strong expertise in Tableau report validation and BI testing. Good working knowledge of Power BI. Hands-on experience validating end-to-end data pipelines from MongoDB → Snowflake → Curated Views → BI Reports. Strong experience in Source-to-Target (S2T) Validation and data reconciliation. Experience validating ETL transformation logic and business rules. Hands-on experience with Slowly Changing Dimensions (SCD Type 2) validation. Strong understanding of Business KPI validation, report testing, and data quality assurance. Experience performing Regression Testing, Functional Testing, and End-to-End Data Validation. Experience working in Agile (Scrum/Kanban) environments. Strong working knowledge of JIRA and QMetry. Excellent analytical, problem-solving, communication, and stakeholder management skills. RESPONSIBILITIES: Design and execute comprehensive test strategies for ETL, Data Warehouse, and BI solutions. Validate end-to-end data flow from MongoDB → Snowflake → Curated Views → Tableau/Power BI Reports. Perform Source-to-Target (S2T) validation to ensure data accuracy and completeness. Validate ETL transformation logic, business rules, and data mapping requirements. Perform data reconciliation between source and target systems. Validate SCD Type 2 implementations and historical data accuracy. Execute functional
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