Test Engineer – Data Migration & Transformation Validation - Java / Python automation along with CI/CD integration

Project description We are looking for an experienced Database Testing Lead with strong expertise in SQL-based backend validation. The candidate will be responsible for validating large data sets, performing file-to-file reconciliation, volume testing, and ensuring accurate data validation from AWS sources to downstream systems (including PNR creation on PID data). API testing experience is required as a secondary skill. Responsibilities Data Migration & Transformation Validation 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 Partner with AI agent onboarding partners to define and execute the onboarding approach for all three UA agents. Establish an automation-first testing strategy for the product and agent-based workflows. Review the product architecture diagrams, and overall solution objectives to understand the end-to-end agent workflow and testing requirements. 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. Skills Must have Primary Skills Strong experience in Database Testing using SQL Expertise in writing complex SQL queries (joins, aggregations, subqueries) and PLSQL Able to build Automation either Using Java / Python along with CI/CD integration Experience in API Testing Experience in File-to-File Data Validation Hands-on experience with Volume Testing / Large Data Set Validation Experience in data reconciliation and backend testing Ability to validate data pipelines and data transformations Experience validating data flow between systems and databases Strong understanding of data integrity, accuracy, and consistency checks Technical Skills SQL (Mandatory) Database platforms such as Oracle, SQL Server, PostgreSQL, or MySQL AWS data validation Experience working with large data volumes Knowledge of data migration and ETL validation Nice to have Secondary Skills API Testing using tools such as Postman, Swagger, or similar tools Experience in AI-driven test automation Understanding of REST APIs and HTTP methods (GET, POST, PUT, DELETE) Ability to validate API responses with database data Knowledge of JSON/XML validation Other Languages English: C1 Advanced Seniority Senior