IND Lead Software Engineer

IND Lead Software Engineer - GCC026 We’re determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals – and to help others accomplish theirs, too. Join our team as we help shape the future. Job Description: Data Quality & Test Automation Engineer Technology Strategy & Enablement (TS&E) | Hyderabad, India Location Hyderabad, India Employment Type Full-Time Experience Level 5-8 Years Organization Technology Strategy & Enablement (TS&E) Position Overview We are seeking a Data Quality & Test Automation Engineer to join TS&E. The role combines data-quality engineering, application and API automation, data-lake validation, and generative AI quality engineering to ensure enterprise data, analytics, and AI-generated insights are accurate, reliable, and trusted. Key Responsibilities Data Quality & Reconciliation • Design and automate source-to-target reconciliation across source systems, ingestion, relational and non-relational databases, data lakes, AWS DocumentDB, APIs, and presentation layers. • Validate data lake ingestion, partitioning, schema evolution, file completeness, and downstream consumption across approved AWS and GCP data services. • Query JSON/document data in AWS DocumentDB or MongoDB-compatible platforms and use SQL to validate relational sources and analytical datasets. • Validate completeness, accuracy, consistency, timeliness, uniqueness, organizational mappings, metrics, charts, filters, and drill-down results. • Perform profiling, anomaly identification, defect triage, and root-cause analysis with Data Engineering and source-system owners. Test Automation & Release Quality • Design and maintain Playwright-based end-to-end automation for web and API experiences. • Build API, integration, regression, smoke, negative, and cross-cloud test coverage. • Create risk-based test plans, cases, traceability, defect documentation, and release-readiness summaries. • Integrate automated tests and data checks into CI/CD pipelines and establish quality gates. • Validate React, Node.js, and Python components using team-standard frameworks. Generative AI Quality & Model Monitoring • Validate AI-generated summaries, explanations, recommendations, and question-and-answer responses against approved source metrics. • Define and track factual accuracy, groundedness, relevance, completeness, consistency, precision, recall, F1, and other applicable quality measures. • Execute regression testing across approved model, prompt, retrieval, and configuration changes using benchmark and golden datasets. • Monitor model and output drift, investigate quality degradation, and document release risk. • Validate GCP- and AWS-hosted models, agent workflows, inference endpoints, and supporting services; GitHub Copilot testing may be included where relevant. Required Qualifications & Skillset • 5-8 years in quality engineering, test automation, data quality, or a related discipline. • Hands-on Playwright expertise and Python and/or JavaScript/TypeScript automation skills. • Experience with source-to-target reconciliation across relational, non-relational, and data-lake platforms. • Experience querying AWS DocumentDB/MongoDB JSON models and aggregation pipelines; working SQL knowledge. • Experience testing REST APIs, enterprise integrations, cloud data pipelines, and AWS/GCP services. • Experience with generative AI evaluation, benchmark datasets, accuracy measures, regression testing, and model/output drift monitoring. • Experience integrating quality controls into CI/CD pipelines. Preferred Qualifications • Experience with S3, Glue, Athena, Lake Formation, Redshift, or comparable GCP data services. • Experience validating executive analytics and organizational drill-downs. • Experience with Rally, Clarity, Workday, GitHub, GitHub Copilot, or similar platforms. • Experience in regulated or audit-driven environments. Success Profile • Builds repeatable validation for data flows, applications, and AI-generated insights. • Identifies defects and model-quality regressions before production. • Provides clear release assessments and communicates risk in business terms. • Works effectively across distributed US and Hyderabad teams. About Us | Our Culture | What It’s Like to Work Here