Analysis Skills, Application Programming Interface (API), Architectural Services, Automation Engineering, Bug Tracking Software, Bug Tracking/Defect Management, Business Analysis, Data Modeling, Data Profiling, Data Quality, Data Warehousing, Database Extract Transform and Load (ETL), Dimensional Modeling, Documentation, Identify Issues, Internet Technology, Microsoft Active Server Page (ASP), Microsoft C# (C Sharp), Model Review, Root Cause Analysis, Snowflake Schema, Software Development, Star Schema, Team Player, Test Automation, Test Case, Test Data, Test Plan/Schedule, Test Requirements, Test Strategy, Testing, Time Management
Position: QA Automation Engineer
Location: Charlotte, NC
Duration: Contract
Rate: DOE
"Knowledge of dimensional modeling and data warehouse concepts, such as star schemas, snowflakes, dimensions, facts
Ensure all sign offs on deliverables (overall test strategy, test plan, test cases, ) and that testing meets governance requirements
Responsible for ensuring quality of their work the work of the entire development team
Strong experience in of the following technologies preferred Web API (MS ASP.Net), MVC, WCF, HTML5, CSS, JavaScript, JSON, SOAP, REST, JQuery, Java , .Net Framework, C#, Ab Initio
Create SIT test cases/test data and perform Test execution
Review Data Models, Data Mappings, Architectural Documentation to create/execute effective SIT Test Plans and SIT test cases
Validates data by running queries in the database and verify that the results match the expectations
Analyzes and troubleshoots erroneous results, determines the root cause of defects, logs the defects in Client Quality Center/ALM 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
Writing queries to extract data for test case data comparison
ETL test validations and checks / Quality checks
Test automation experience is huge plus
Data profiling is plus
Understanding of ETL requirements (source-to-target mappings)\ "