Job Summary
Client is looking for a Contractor who will conduct data migration automated testing. Data migration automated testing is a verification process of migration of the legacy system to the new system with minimal disruption/downtime, with data integrity and no loss of data, while ensuring that all the specified functional and non-functional aspects of the application are met post-migration.
Objectives(s)
client to list objectives for the project engagement
- Contractor shall successfully perform automated data level validation testing
- Contractor shall perform automated Data Quality Validation Testing.
Work Description
client to list and provide a detailed description of the project deliverables.
- Automated testing verifies that data has been migrated from multiple databases to a common database without any discrepancies.
- Automated Business/Scenarios based Validations
- Automated Data and Reports Integrity Validations
- Automated Data Performance Validations
Expectations
- 8+ year of SQL and Database Expertise
Why it matters: Data migration testing heavily involves validating data integrity, completeness, and transformation logic.
Key skills:
- Writing complex SQL queries
- Understanding of relational databases (e.g., SQL Server, Oracle, PostgreSQL)
- Data comparison and reconciliation techniques
- Scripting and Programming (e.g., Python, Java, C#, JMeter)
Why it matters: Automation of data validation and transformation checks often requires custom scripts.
Key skills:
- Writing reusable test scripts
- Parsing and comparing large datasets
- Integrating with APIs or ETL tools
- Test Automation Frameworks
Why it matters: Automating regression tests for migrated data ensures consistency and saves time.
Key skills:
- Experience with tools like Selenium, TestNG, PyTest, or JUnit
- Building data-driven test cases
- CI/CD integration (e.g., Azure DevOps, GitHub)
- ETL and Data Pipeline Testing
Why it matters: Understanding how data is extracted, transformed, and loaded is crucial for validating the migration process.
Key skills:
- Familiarity with ETL tools (e.g., SSIS, Informatica, Azure Dataverse)
- Validating transformation logic
- Monitoring and logging data flows
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