Posted on: 25/08/2026
Role : Senior Test Analyst Quality Engineering / QA ETL
Location : Gurugram, India
Experience : 710 Years
Mode of Interview : Virtual + In-person
Employment Type : Full-time
Key Responsibilities :
1. ETL & Data Testing :
- Design and execute comprehensive test strategies for ETL pipelines, data migration, data transformation, and data integration processes.
- Validate data movement across source, staging, transformation, and target systems.
- Verify data completeness, accuracy, consistency, integrity, and transformation rules.
- Develop source-to-target mapping validation scenarios.
- Perform data reconciliation between upstream and downstream systems.
- Validate transformation logic, business rules, calculations, aggregations, and derived fields.
- Identify data anomalies, missing records, duplicate records, truncation issues, and transformation discrepancies.
- Validate incremental and full data loads.
- Test ETL workflows for positive, negative, boundary, and exception scenarios.
- Perform regression testing whenever ETL mappings, business rules, schemas, or data pipelines are modified.
- Analyze failed ETL jobs and work with Data Engineers and Developers for resolution.
2. SQL & Database Testing :
- Demonstrate strong hands-on expertise in SQL for database and ETL validation.
- Write complex SQL queries involving joins, subqueries, CTEs, aggregations, window functions, and data comparison techniques.
- Validate data across multiple database tables and schemas.
- Perform backend data validation independently without relying solely on UI validation.
- Compare source and target datasets to identify data mismatches.
- Validate record counts, null values, duplicate records, referential integrity, and data quality.
- Develop reusable SQL queries for regression and data validation.
- Perform database testing across different stages of the data pipeline.
- Support root-cause analysis of data-related defects using database queries and logs.
3. Snowflake Testing :
- Perform hands-on testing and validation of data stored in Snowflake.
- Validate Snowflake tables, views, schemas, and data transformation processes.
- Execute SQL queries in Snowflake for data reconciliation and validation.
- Validate data ingestion into Snowflake from upstream systems.
- Verify transformation and business rules implemented within Snowflake.
- Perform source-to-target data comparison between legacy/upstream databases and Snowflake.
- Validate incremental loads, historical data, and data refresh processes.
- Identify data quality issues and provide actionable findings to development/data engineering teams.
- Support regression testing for Snowflake-based data pipelines.
4. API Testing :
- Design and execute API test scenarios for REST-based integrations.
- Perform API testing using Postman and similar tools.
- Validate REST APIs using JSON and XML request/response payloads.
- Verify HTTP methods, status codes, headers, authentication, request parameters, and response structures.
- Validate positive, negative, boundary, and error-handling scenarios.
- Perform API integration testing between internal applications and external invoicing/tax platforms.
- Validate data consistency between API responses and backend databases.
- Perform end-to-end validation across API, application, database, and downstream systems.
- Analyze API logs and integration failures for root-cause identification.
5. Invoice & Financial Transaction Testing :
- Validate end-to-end invoice ingestion, processing, transformation, and transmission workflows.
- Verify invoice data across upstream applications, middleware/API layers, databases, and downstream systems.
- Validate invoice fields, calculations, tax information, currencies, dates, customer/vendor details, and transaction attributes.
- Validate country-specific invoice formats and regulatory requirements.
- Test different invoice types, transaction scenarios, and exception conditions.
- Perform reconciliation between source invoices and processed/transmitted invoices.
- Validate failed, rejected, duplicate, and partially processed transactions.
- Work with business teams and vendors to resolve invoice-processing discrepancies.
- Support testing for financial transaction processing and integration programs.
6. Automation Testing :
- Develop and maintain automated test scripts for functional, API, ETL, database, and regression testing.
- Identify suitable test scenarios for automation based on risk, frequency, and business criticality.
- Contribute to the development and enhancement of automation frameworks.
- Integrate automated tests into CI/CD pipelines wherever applicable.
- Execute automated regression suites and analyze failures.
- Maintain reusable automation components and test utilities.
- Improve regression coverage through automation.
- Generate execution reports and quality metrics.
- Collaborate with developers and QA engineers to improve automation reliability and maintainability.
7. Python :
- Utilize Python for test automation, data validation, test utilities, and scripting.
- Develop Python scripts for database validation and data comparison.
- Automate repetitive data-quality and reconciliation activities.
- Develop reusable utilities for API and ETL testing.
- Use Python to analyze large datasets and identify anomalies.
- Support automation framework development and maintenance.
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Posted by
Posted in
Quality Assurance
Functional Area
Big Data / Data Warehousing / ETL
Job Code
1665699