Teams at Nexaminds

Leads enterprise quality engineering and test automation strategy across UI, API, integration, performance, and data layers. Architects Java-based automation frameworks, establishes CI/CD quality gates, drives ETL and data validation, and governs responsible AI adoption in QA. The role leads QA transformation initiatives, mentors engineers, collaborates with Engineering, DevOps, Data, and Product teams, and evaluates AI-enabled testing capabilities.

Design and lead scalable data engineering solutions using Databricks and Azure. Establish enterprise data modeling and engineering standards, architect pipelines and integrations, improve platform reliability and performance, guide modernization and cloud migrations, troubleshoot complex issues, and mentor data engineers while ensuring security, quality, and governance.

Design, develop, and maintain scalable data pipelines, models, ingestion, transformation, and integration solutions using Databricks and Microsoft Azure. Troubleshoot performance and data quality issues, optimize workflows, support migrations and modernization, and collaborate with architecture and engineering teams. Translate business requirements into technical solutions while following security, governance, quality, and engineering best practices.