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Fractal Analytics Private Limited is seeking a Senior Test Engineer to rigorously validate data pipelines, ensure data integrity, and drive quality in analytics solutions. You will design test strategies, develop comprehensive test plans, and collaborate with data engineers and product owners to ensure alignment with business needs.
The role focuses on SQL-driven data validation, end-to-end ETL testing, and optimizing automated validation suites to improve efficiency and coverage.
It's fun to work in a company where people truly BELIEVE in what they are doing! We're committed to bringing passion and customer focus to the business.
Role Summary Mandatory: SQL, Data Validation, ETL/Data Pipeline Testing, Test Strategy & Planning, Test Case Design, Data Analytics, Automation Testing, Stakeholder Collaboration, Defect Management.
Define and implement comprehensive test strategies for data engineering and analytics solutions. Develop test plans, test approaches, and validation frameworks aligned with project objectives and business requirements. Identify testing scope, risks, dependencies, and mitigation plans. Ensure appropriate test coverage across functional, integration, system, regression, and data validation testing.
Analyze business requirements and data specifications to create detailed test scenarios and test cases. Execute functional, integration, regression, and user acceptance support testing activities. Validate data transformations, calculations, aggregations, and business rules across data pipelines. Ensure testing activities align with defined quality standards and acceptance criteria.
Perform extensive SQL-based data validation and reconciliation across source and target systems. Validate data accuracy, completeness, consistency, and integrity throughout the data lifecycle. Verify KPIs, metrics, reports, dashboards, and analytical outputs against business expectations. Analyze large datasets to identify anomalies, inconsistencies, and quality issues.
Test end-to-end ETL and ELT processes across data ingestion, transformation, and consumption layers. Validate data movement across multiple systems and platforms. Ensure data pipelines process information according to defined business and technical requirements. Test error-handling, exception management, and data recovery scenarios.
Identify, document, track, and manage defects throughout the testing lifecycle. Perform detailed root cause analysis for data discrepancies and functional issues. Collaborate with development and data engineering teams to resolve defects efficiently. Verify fixes and support regression testing activities.
Identify opportunities to automate repetitive testing and data validation activities. Contribute to the development and maintenance of automated test suites and validation frameworks. Recommend improvements to testing processes, methodologies, and tools to increase efficiency and coverage. Support quality engineering best practices and continuous testing initiatives.
Work closely with Business Analysts, Data Engineers, Product Owners, and business users to understand requirements and expected outcomes. Participate in requirement reviews, solution discussions, and testing workshops. Communicate testing progress, risks, defects, and quality metrics to stakeholders. Support user acceptance testing and production readiness activities.
Experience Level Senior Level