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Salary
≈ $13k – $30k per year (Estimated)
Location
In office (Gurgaon)
Experience
6+ years exp
Employment
Full-Time

First seen by Alion on Oct 9, 2026.

Overview
Company
Impact
Profile match
Turn AI Velocity into Assured Outcomes IGT Solutions is now Atain. Variability across people, processes, and platforms makes outcomes unpredictable. Atain eliminates variability, orchestrates expertise, and accelerates AI-driven velocity to deliver consistent, assured outcomes.

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

Experience: 6–10 Years

Location: Gurgaon Hybrid

Interested candidate please share resume on [HIDDEN TEXT]

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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