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Role at a glance
You will
The ideal candidate should possess strong expertise in ETL testing, SQL, data validation, and data quality assurance across large-scale…
Analyze business requirements, source-to-target mapping documents, and technical specifications.
Design, develop, and execute comprehensive ETL test cases, test plans, and test scenarios.
Experience
4–6 years
Must-have skills
AgileAzure DevOpsAzure SQLData WarehousingETLJIRA
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Job description
Location: Bangalore, India
Role Overview We are looking for an experienced ETL Testing Engineer with 4–6 years of hands-on experience in validating Data Warehouse and ETL solutions. The ideal candidate should possess strong expertise in ETL testing, SQL, data validation, and data quality assurance across large-scale enterprise data platforms. Key Responsibilities
Analyze business requirements, source-to-target mapping documents, and technical specifications.
Design, develop, and execute comprehensive ETL test cases, test plans, and test scenarios.
Validate data extraction, transformation, and loading processes across multiple source systems.
Perform data reconciliation and data quality checks between source and target systems.
Write complex SQL queries for database testing and data validation.
Verify data integrity, completeness, consistency, and accuracy throughout the ETL lifecycle.
Validate data warehouse and data mart implementations.
Identify, log, track, and retest defects using defect management tools.
Collaborate with ETL developers, business analysts, data engineers, and stakeholders to resolve data issues.
Participate in release validation, regression testing, and production support activities.
Prepare test reports and communicate testing status to project stakeholders.
Required Skills
4–6 years of experience in ETL/Data Warehouse testing.
Strong knowledge of ETL concepts and Data Warehousing methodologies.
Proficiency in SQL with experience writing complex joins, subqueries, aggregations, and performance validation queries.
Experience testing ETL tools such as:
Informatica PowerCenter
Talend
Azure Data Factory (ADF)
SSIS
Datastage
Strong knowledge of database platforms:
SQL Server
Oracle
PostgreSQL
Snowflake
Azure SQL
Experience validating large datasets and performing data reconciliation.
Expertise in data quality, data profiling, and data transformation validation.
Familiarity with Agile/Scrum methodologies.
Experience with defect tracking tools such as JIRA or Azure DevOps.
This guide is for Indian job seekers preparing for SQL rounds in data analyst, data engineer, backend developer and database roles, from freshers to experienced professionals. It has 60 questions in three levels: easy covers joins, grouping and NULLs; medium covers window functions, CTEs, indexes and isolation levels; hard covers locking, MVCC, query tuning and classic puzzles such as login streaks and medians. Answers use ANSI SQL, with MySQL 8 and PostgreSQL notes where the two differ. Write each query against your own sample tables first, then compare your result with the sample answer.
Questions you may be asked
What is the difference between WHERE and HAVING?
What is the difference between DELETE, TRUNCATE and DROP?
What is the difference between an INNER JOIN and a LEFT JOIN?
What is the difference between a primary key and a unique key?
