CDP Data Quality Testing

Position Title: QA Engineer |||

About Americana Restaurants International PLC

Americana Restaurants International PLC is a pioneering force in the MENA region and Kazakhstan's Out-of-Home Dining industry, ranking among the world's leading operators of Quick Service Restaurants (QSR) and casual dining establishments. With an extensive portfolio of iconic global brands and a dominant regional presence, we have been driving growth and innovation for over 60 years.

Our expansive network of 2,600+ restaurants spans 12 countries throughout the Middle East, North Africa, and Kazakhstan — from Kazakhstan in the east to Morocco in the west — powered by a team of 40,000+ talented individuals committed to delivering exceptional food, superior service, and memorable experiences.

In line with our vision for innovation and operational excellence, we have established our Center of Excellence in Mohali, India. This state-of-the-art facility plays a pivotal role in Product Development, IT, Digital, AI, and Analytics, while implementing global IT best practices. Serving as a strategic hub, it strengthens our technology backbone and drives digital transformation across our worldwide operations.

Your Impact:

1. Data Quality Testing:
2. Perform data validation to ensure the accuracy, integrity, and consistency of data across all stages of the ETL pipeline (Extract, Transform, Load).
3. Verify that data transformations are executed correctly and that business rules are applied properly.
4. Perform data reconciliation between source systems and target data stores to ensure completeness and correctness.
5. Automation and Scripting:
6. Design and implement automated test scripts for validating ETL processes and Big Data pipelines.
7. Develop and maintain test automation frameworks for scalable and repeatable testing processes.
8. Work with CI/CD pipelines to ensure automated testing is integrated into the build and deployment process for continuous quality validation.
9. Performance and Scalability Testing:
10. Conduct performance testing on ETL processes and Big Data pipelines to assess scalability and efficiency.
11. Monitor and evaluate the data processing speed, resource utilization, and overall system performance under varying loads.
12. Collaborate with data engineers to optimize pipeline performance based on test results.
13. Big Data Platform Validation:
14. Ensure data accuracy and consistency in large-scale distributed systems like Hadoop, Spark, Hive, Presto, or Kafka.
15. Perform end-to-end testing across the data flow to validate the transformation, integration, and storage of large datasets.
16. Validate the integration of ETL pipelines with Big Data tools and databases (e.g., HDFS, NoSQL, relational databases).
17. Data Integration and Automation Testing:
18. Validate integration between multiple data sources (relational databases, NoSQL databases, APIs, external data systems) and the Big Data platform.
19. Test data exchange across heterogeneous systems, ensuring data is transferred, transformed, and loaded without errors or data loss.
20. Bug Identification and Troubleshooting:
21. Identify, document, and track defects found during testing and work closely with the development team to resolve issues.
22. Perform root cause analysis for defects in data pipelines or data quality issues and ensure they are properly addressed.
23. Retest fixed issues and ensure regression testing is done to verify that changes did not impact existing workflows.
24. Documentation and Reporting:
25. Provide regular test progress reports and communicate the status of testing efforts, including any critical issues or blockers, to stakeholders.

What You Bring

• Bachelor's degree in computer science, Information Technology, Engineering,
• 4 + years of experience in QA testing with a focus on CDP, ETL processes and Big Data platforms.
• Strong knowledge of ETL processes and understanding of data pipeline architectures (e.g., Hadoop, Spark, Kafka, Hive, Presto).
• Experience with Big Data platforms (HDFS, Hive, HBase, Presto, etc.) and distributed computing environments.
• Proficiency in writing and executing SQL queries to validate data across various platforms.
• Experience with automation frameworks and tools for ETL testing, such as Selenium, JUnit, TestNG, PyTest, or similar.
• Familiarity with JIRA, Confluence, and other collaboration tools for issue tracking and test management.
• Strong scripting skills in languages such as Python, Java, Scala, or Bash.
• Knowledge of CI/CD processes and integration testing in an Agile environment.
• Excellent analytical and problem-solving skills to identify and resolve issues related to data quality, transformation, and integration.
• Strong communication skills and the ability to collaborate effectively with cross-functional teams.