• Own and drive end-to-end sales cycles for large QE opportunities (USD 5M+) • Consistently achieve and exceed annual QE revenue targets • Build and maintain a strong pipeline of exclusive and sole-sourced QE deals • Drive long-term managed services, annuity-based, and transformation-led QE engagements • Collaborate with the account Client Partners and enabled channels for QE • Create RFP, RFI, and RFQ responses for QE opportunities • Shape differentiated QE solution strategies covering automation, AI-driven QE, QE for AI, performance engineering testing, data testing, and continuous testing • Drive pricing, commercials, value engineering, and deal structuring • Collaborate closely with capability/practice and delivery teams to create winning proposals • Build trusted advisor relationships with CXOs, CIOs, CTOs, Heads of Engineering, and Quality Engineering Leaders • Act as executive sponsor for strategic QE accounts • Lead executive presentations and contract negotiations • Position QE as a business enabler and AI-led transformation driver • Represent the organization in industry QE forums, conferences, roundtables, and client events • Publish thought leadership content, including blogs, whitepapers, and articles on Quality Engineering, AI in testing, and digital quality trends • Partner with the India practice & capability team and marketing teams on QE branding, campaigns, analyst interactions, and GTM initiatives • Contribute to QE marketing strategies and market messaging • Identify emerging QE trends and influence service offerings and roadmap with the capability development team

• Design, implement, and maintain automated data quality checks to validate accuracy, completeness, consistency, and timeliness across data pipelines and analytics layers. • Implement proactive monitoring and alerting for data pipelines to detect anomalies, schema changes, or data drift. • Validate business logic, calculations, aggregations and filters in BI tools to ensure alignment with business definitions. • Perform end-to-end testing of data pipelines, including ingestion, transformation (ETL/ELT), semantic layers and reporting outputs. • Conduct regression testing for schema changes, pipeline updates, and BI model modifications. • Integrate data quality checks into CI/CD pipelines and production monitoring. • Monitor data freshness, volume, and distribution to proactively detect and alert on failures or quality degradation. • Partner with data engineering, analytics, and product teams to define data acceptance criteria and quality thresholds.

• Support a Power Platform and Azure-based implementation • Focus on data migration and quality assurance • Hands-on testing experience across Power Platform solutions and migrated legacy data

• Develop, document, and maintain comprehensive test cases for iOS, Android, and web applications • Execute manual testing across multiple platforms and devices to identify bugs, usability issues, and inconsistencies • Perform thorough regression testing to ensure existing functionality remains intact after updates • Produce detailed test coverage reports and metrics to track quality assurance progress • Utilize cloud-based testing platforms such as BrowserStack to test across various device configurations and OS versions • Design and implement automated test scripts to improve testing efficiency and coverage • Collaborate with development teams to reproduce, document, and track defects through resolution • Participate in sprint planning and provide estimates for testing efforts • Contribute to the continuous improvement of QA processes and methodologies