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Strong employer brand and metro location but senior, niche database QA specialization reduces candidate density.
Database and test-data skills are transferable, but finance platform familiarity increases domain specificity.
Mandatory nine years, specific DB platforms, QA and data-governance skills make filters highly stringent.
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Own daily operational support and readiness of end-to-end QA and non-production database environments across multiple platforms, ensuring availability, configuration, and data integrity for application release validation.
Lead troubleshooting and resolution of environment-related incidents, coordinating fixes and communicating status to stakeholders to maintain test cycle continuity.
Define, deploy, and govern a unified data platform for QA that supports self-service data provisioning, synthetic data generation, and integration with CI/CD pipelines for automation and scalable testing workflows.
Minimum 9 years of experience as a Database Analyst with hands-on support of QA, UAT, integration staging or non-production database environments.
Strong SQL skills with experience in data validation, comparison, and troubleshooting.
Practical experience with at least two database/cache platforms among SQL Server, Oracle, Postgres, Cosmos DB, Snowflake, RocksDB, or Redis.
Familiarity with cloud environments (Azure), Kubernetes deployments, workflow orchestration, synthetic test data generation, and CI/CD integration.
Experienced in managing complex QA and integration testing environments involving multiple database technologies and automation.
Capable of designing and implementing data-driven automation frameworks and synthetic data solutions to enable autonomous testing workflows.
Comfortable working in data-intensive environments with strong understanding of data security, privacy, and compliance related to sensitive or PII data.