What are the responsibilities and job description for the Informatica PowerCenter QA (Hybrid) position at Boston Data Pro, LLC?
Role: Informatica PowerCenter QA (Hybrid).
Location: Tampa, FL (Hybrid)
Looking for QA with 5 years Informatica PowerCenter, Oracle SQL server and MS SQL server.
This role focuses on testing the ETL (Extract, Transform, Load) processes developed using Informatica PowerCenter. The primary goal of this role is to ensure that the ETL pipeline works as expected, with data being accurately extracted, transformed, and loaded into the target systems, while meeting business and technical requirements. A QA role involves ensuring the correctness, completeness, and performance of the data processing flows.
· Test Plan Development: Develop a comprehensive test plan that outlines the testing scope, test cases, test data, and the expected outcomes for various ETL processes.
· Test Strategy: Define the testing approach for different types of tests, including data validation, transformation testing, and performance testing.
· Develop and implement automated test scripts where possible to validate ETL processes. This can be achieved through custom scripts or using tools like Informatica Test Data Management or third-party testing tools.
· Work closely with ETL Developers, Data Architects, and Business Analysts to understand business rules and requirements, as well as to communicate issues found during testing.
· Verify individual ETL components such as mappings, transformations, and sessions to ensure they perform correctly in isolation.
· Test the integration of various ETL components in workflows and ensure they function correctly when combined.
· Perform end-to-end validation of the entire ETL process, from data extraction through transformation and loading into the target system.
· Ensure that changes made to the ETL processes do not break existing functionality or introduce new defects.
· Validate the correctness of data transformations, ensuring that the data is correctly extracted, transformed, and loaded into the target database.
· Evaluate the performance of ETL jobs to ensure they run efficiently, particularly with large datasets. This may involve testing job execution times and handling of large volumes of data.
· Familiarity with scripting languages like Python or Shell scripting to automate repetitive test cases.
