The Role
Performs ETL and data warehouse testing, validating data pipelines, transformations, source-to-target mappings, reconciliations, data quality, batch jobs, and database loads. Creates test scenarios, executes functional and regression testing, manages defects, and collaborates with technical teams to resolve data issues. The role also supports test automation and requires strong SQL, ETL, dimensional modeling, and slowly changing dimension knowledge.
Summary Generated by Built In
We are looking for an experienced ETL QA Engineer / Data QA Engineer responsible for validating data pipelines, ETL processes, data transformations, and data warehouse solutions. The ideal candidate should have strong SQL skills and hands-on experience with ETL testing, data validation, and defect management.
- Analyse business and technical requirements and prepare test scenarios and test cases.
- Perform ETL testing for data extraction, transformation, and loading processes.
- Validate source-to-target data mappings and transformation rules.
- Perform data validation using complex SQL queries.
- Verify data completeness, accuracy, consistency, and integrity across source and target systems.
- Test data pipelines, batch jobs, interfaces, and data warehouse loads.
- Perform data reconciliation between source systems, staging areas, and target databases.
- Validate incremental loads, full loads, historical data, and slowly changing dimensions (SCD).
- Test error handling, duplicate records, null values, boundary conditions, and data-quality rules.
- Execute regression, integration, system, and end-to-end testing.
- Identify, document, track, and retest defects using tools such as Jira or similar defect-management systems.
- Work closely with developers, ETL developers, business analysts, and data engineers to resolve data-related issues.
- Participate in test planning, estimation, execution, and reporting.
- Contribute to automation of repetitive data-validation and regression test scenarios where applicable.
Requirements
- Strong hands-on experience in ETL/Data Warehouse Testing.
- Excellent knowledge of SQL and relational databases.
- Understanding of ETL concepts and data warehouse architecture.
- Experience with source-to-target mapping and data reconciliation.
- Knowledge of dimensional modelling, fact and dimension tables.
- Understanding of SCD Types 1 and 2.
- Experience testing batch jobs and data pipelines.
- Good understanding of SDLC and STLC.
- Experience with defect-management and test-management tools such as Jira, ALM, or similar.
- Strong analytical and problem-solving skills.
- Experience with ETL tools such as Informatics, SSIS, DataStage, or Azure Data Factory.
- Experience with cloud data platforms such as Snowflake, AWS, or Azure.
- Knowledge of Python or another scripting language for test automation.
- Experience with CI/CD and automated testing frameworks.
- Exposure to data-quality and data-governance concepts.
- Experience testing APIs or downstream reporting/BI systems.
5-7 years of experience in ETL Testing, Data Warehouse Testing, Data QA, or a related role.
EducationBachelor’s degree in Computer Science, Information Technology, Engineering, or a related field.
- Strong SQL and data-analysis skills
- ETL
Skills Required
- Hands-on experience in ETL and data warehouse testing
- Strong SQL and relational database knowledge
- Understanding of ETL concepts and data warehouse architecture
- Experience with source-to-target mapping and data reconciliation
- Knowledge of dimensional modeling, fact tables, and dimension tables
- Understanding of Slowly Changing Dimensions Types 1 and 2
- Experience testing batch jobs and data pipelines
- Understanding of SDLC and STLC
- Experience with defect-management and test-management tools such as Jira, ALM, or similar
- Strong analytical and problem-solving skills
- Five to seven years of experience in ETL testing, data warehouse testing, data QA, or a related role
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field
- Experience with ETL tools such as Informatica, SSIS, DataStage, or Azure Data Factory
- Experience with cloud data platforms such as Snowflake, AWS, or Azure
- Knowledge of Python or another scripting language for test automation
- Experience with CI/CD and automated testing frameworks
- Exposure to data-quality and data-governance concepts
- Experience testing APIs or downstream reporting and BI systems
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The Company
What We Do
Blackbuck Insights is a global data and AI consultancy providing data engineering services, cloud modernization, AI activation, and platform operations. The company helps enterprises modernize legacy environments, migrate and scale data platforms, build AI-enabled business applications, and establish trusted data foundations for analytics and intelligent decision-making. Its services support organizations seeking reliable, performant, and scalable technology solutions.
