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DB Tester

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Onsite

DB Tester

Atain

DB Tester

Skills

SQL QueriesTesting & QAAI

19 days ago

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Important information


Contract type:

Permanent

Location:

Gurugram, Haryana, India

Work mode:

Onsite

Published on:

8 October 2026

What they need


Job Description Role: Test Engineer – Data Migration & Transformation Validation

Experience: 6–10 Years

Location: Gurgaon Hybrid

Interested candidate please share resume on [email protected]

Test Engineer – Data Migration & Transformation Validation (Must Have)

  • Lead testing efforts for large-scale data transformation and migration initiatives involving millions of records across enterprise Network Operation platforms.

  • Design and execute comprehensive data validation strategies to ensure data accuracy, completeness, consistency, and integrity during migrations.

  • Develop complex SQL queries and automated validation scripts to reconcile source and target systems at scale.

  • Validate ETL/ELT processes, transformation rules, data mappings, and business logic across multiple data domains.

  • Perform end-to-end testing of batch, real-time, and incremental data migration workflows.

  • Identify, analyze, and troubleshoot data quality issues, migration defects, duplicates, missing records, and transformation anomalies.

  • Collaborate closely with data engineers, architects, business analysts, and application teams to define test strategies and acceptance criteria.

  • Generate detailed data quality metrics, reconciliation reports, and migration readiness assessments for stakeholders.

  • Drive best practices in database testing, automation, and data quality engineering to ensure successful delivery of enterprise migration programs.

AI Agent Onboarding & Test Automation (Good to Have)

  • Establish an automation-first testing strategy for the product and agent-based workflows.

  • Identify opportunities to use AI-driven test automation to improve test coverage, execution efficiency, and agent workflow validation.

  • Collaborate with development, architecture, AI partners, and QA teams to embed DB automation & AI agent into the product development lifecycle.

  • Define test scenarios and validation strategies for AI-agent-based workflows, covering functional, integration, data, and end-to-end validation.

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