Tata Consultancy Services
Skill: Sr Data tester- MDM Domain
Must Have Technical/Functional Skills: Strong SQL and database skills: Essential for querying, analyzing, and validating data within relational databases. ETL testing experience: Familiarity with ETL processes and tools is crucial for testing data integration pipelines. Data warehousing knowledge: Understanding of data warehousing principles and concepts is important for testing data within data warehouse environments. Data quality and governance experience: Knowledge of data quality concepts and practices is essential for ensuring data accuracy and reliability. Test automation skills: Experience with automation tools and frameworks is necessary for automating test cases and improving testing efficiency. Strong analytical and problem-solving skills: Ability to analyze data, identify anomalies, and troubleshoot issues is crucial. Excellent communication and collaboration skills: Effective communication and collaboration with various teams are essential for resolving data issues and ensuring data quality. Experience with Agile/Scrum methodologies: Familiarity with Agile/Scrum methodologies is often preferred for working in fast-paced development environments. Roles & Responsibilities:
Data Quality Assurance: Developing and executing comprehensive test plans to identify and address data quality issues within the MDM system, including duplicate data, inconsistencies, and errors. Test Case Development: Creating and documenting detailed test cases and scenarios for validating MDM data against business rules, data models, and specifications. Data Validation: Performing end-to-end testing of data flows and processes within the MDM solution to ensure data integrity and completeness across all integrated systems. Root Cause Analysis: Investigating and resolving data quality problems, working with data owners and technical teams to implement corrective actions. MDM Tools and Technologies: Possessing strong knowledge of MDM platforms like Informatica, SAP, Oracle, and other relevant tools. Collaboration: Working closely with business stakeholders, data architects, developers, and other QA teams to ensure the MDM system meets business requirements and data governance standards. Documentation: Documenting data quality processes, standards, and findings, according to aijobs.net. Communication: Clearly communicating test results and data quality issues to both technical and non-technical stakeholders. Salary Range - $90,000-$110,000 a year
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Must Have Technical/Functional Skills: Strong SQL and database skills: Essential for querying, analyzing, and validating data within relational databases. ETL testing experience: Familiarity with ETL processes and tools is crucial for testing data integration pipelines. Data warehousing knowledge: Understanding of data warehousing principles and concepts is important for testing data within data warehouse environments. Data quality and governance experience: Knowledge of data quality concepts and practices is essential for ensuring data accuracy and reliability. Test automation skills: Experience with automation tools and frameworks is necessary for automating test cases and improving testing efficiency. Strong analytical and problem-solving skills: Ability to analyze data, identify anomalies, and troubleshoot issues is crucial. Excellent communication and collaboration skills: Effective communication and collaboration with various teams are essential for resolving data issues and ensuring data quality. Experience with Agile/Scrum methodologies: Familiarity with Agile/Scrum methodologies is often preferred for working in fast-paced development environments. Roles & Responsibilities:
Data Quality Assurance: Developing and executing comprehensive test plans to identify and address data quality issues within the MDM system, including duplicate data, inconsistencies, and errors. Test Case Development: Creating and documenting detailed test cases and scenarios for validating MDM data against business rules, data models, and specifications. Data Validation: Performing end-to-end testing of data flows and processes within the MDM solution to ensure data integrity and completeness across all integrated systems. Root Cause Analysis: Investigating and resolving data quality problems, working with data owners and technical teams to implement corrective actions. MDM Tools and Technologies: Possessing strong knowledge of MDM platforms like Informatica, SAP, Oracle, and other relevant tools. Collaboration: Working closely with business stakeholders, data architects, developers, and other QA teams to ensure the MDM system meets business requirements and data governance standards. Documentation: Documenting data quality processes, standards, and findings, according to aijobs.net. Communication: Clearly communicating test results and data quality issues to both technical and non-technical stakeholders. Salary Range - $90,000-$110,000 a year
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