Senior QA Automation Engineer - Norwegian Cruise Line Holdings Ltd - Miami, FL
Norwegian Cruise Line Holdings Ltd
JOB SUMMARY: Responsible for designing, developing, and executing automated testing solutions and comprehensive test plans related to Source System and Business Data Products to validate the integrity, accuracy, and consistency of enterprise data across multiple business domains. This role ensures the quality of data processed through ETL pipelines and data modeling scripts across platforms such as Oracle, SQL Server, and Snowflake. The QA Automation Engineer collaborates with data engineering, QA, and business teams to support scalable, reliable, and high quality data delivery across the organization.
DUTIES & RESPONSIBILITIES:
Design and Develop Automated Data Quality Tests: Create reusable, automated tests to validate data ingestion, transformations, and loading across Oracle, SQL Server, and Snowflake.Validate data integrity, completeness, schema conformity, and business logic through all layers - from raw landing zone to curated data products.Ensure End-to-End Data Pipeline Validation: Automate testing for ETL/ELT processes, including data staging, cleansing, fact and dimension population, and final consumption layers.Monitor transformations and data flows between platforms (Oracle - Snowflake, SQL Server - Snowflake, etc.).Leverage Snowflake-Specific Testing Capabilities: Use Snowflake's native SQL features (e.g., streams, tasks, time travel, variant types) in test development.Automate regression and functional testing for Snowflake data models, stored procedures, and materialized views.Build and Maintain a Cross-Platform Test Framework: Extend or integrate test automation frameworks compatible with Oracle, SQL Server, and Snowflake. Apply data validation tools to verify transformations.Utilize TestRail for Test Case Management: Design, document, and maintain test cases and test plans in TestRail.Track test execution, report defects, and maintain traceability across automated and manual test cases.Collaborate Across Data Engineering and Modeling Teams: Partne