4-6 years of experience in ETL and Data Warehouse testing
Proficient in writing SQL Queries to extract data as per the test cases and perform data comparison
Create SIT test cases/test data and perform Test execution
Knowledge of dimensional modeling and data warehouse concepts, such as star schemas, snowflakes, dimensions and facts
Review Data Models, Data Mappings, Architectural Documentation to create/execute effective SIT Test Plans and SIT test cases
Analyzes and troubleshoots erroneous results, determines the root cause of defects, logs the defects in HP Quality Center/ALM/Jira or other Test Management tool and enables defect management, including working with the development team on the resolution of Software related defects
Works closely with software development team (Business Analysts, Developers & other testers) to ensure timely and effective testing effort
Ensure all sign offs on deliverables (overall test strategy, test plan, test cases, ) and that testing meets governance requirements
Solid understanding of databases and systems and the ability to communicate effectively across groups
Self Starter, with strong confidence level
Flexible in thought and creative in approach to testing
Experienced in an Onshore/Offshore model, ability to work independently and with a team.
Excellent Communication, Analytical and Problem solving skills
PREFERRED / GOOD TO HAVE
Knowledge of ETL automation tool such as Query surge
Basic understanding of big data technologies
Cloud technology knowledge/experience – Azure, AWS, GCP
Experience in various databases – Oracle, Teradata, Snowflake etc.
ROLES / RESPONSIBILITIES:
Design, implement, and continuously expand data pipelines by performing extraction, transformation, and loading activities
Gather requirements and business process knowledge in order to transform the data in a way that’s geared towards the needs of end users
Maintain and improve already existing processes
Ensure that the data architecture is scalable and maintainable
Work with the business in designing and delivering correct, high quality data
Investigate data to identify potential issues within ETL pipelines, notify end-users and propose adequate solutions
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