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SDET with 4+ years in API Automation, Cloud QA & Fintech
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Software Development Engineer in Test (SDET) with 4+ years of hands-on experience designing scalable automation frameworks for REST APIs, backend microservices, and cloud data pipelines in Fintech and Banking domains. Proven expertise in API automation (Postman, Bruno), GCP data validation (BigQuery, GCS, Pub/Sub), Playwright-based UI automation, and CI/CD pipeline integration. Strong collaborator in Agile/Scrum environments with a consistent track record of reducing regression cycle times, catching critical defects pre-production, and driving quality improvements across distributed systems.
Bangalore University
Bachelor of Science · Computer Science
N/A – Present
Infosys Pvt. Ltd.
Quality Engineering Analyst (SDET)
December 1, 2021 – Present
Bengaluru, Karnataka, India
Event-Driven Messaging QA — RabbitMQ & Pub/Sub Validation
November 1, 2025 – June 30, 2026
Validated RabbitMQ and Google Pub/Sub message flows for Charles Schwab's real-time trade event processing — covering order placement, execution, and confirmation events. Verified delivery guarantees, payload accuracy, message sequencing, retry logic, and dead-letter queue handling under normal and failure conditions. Designed chaos-style test scenarios simulating consumer failures, network delays, and out-of-order message delivery to validate system resilience. Built message schema contract validation tests to catch breaking changes before deployment.
Web Application Automation — Client Portal (Playwright)
September 1, 2025 – June 30, 2026
Built a Playwright-based automation framework for Charles Schwab's client-facing wealth management portal — covering account dashboard, trade execution, and portfolio views. Reduced manual web regression effort by ~60%, enabling faster and safer release cycles across sprint deliveries. Implemented page object model (POM) design pattern ensuring maintainability and reusability across multiple application modules. Automated smoke test suite triggered on every deployment — providing instant feedback on critical user journeys within 15 minutes of each release.
GCP Data Pipeline QA — Trade & Account Data Ingestion
January 1, 2025 – June 30, 2026
Owned end-to-end QA for Charles Schwab's GCP data ingestion pipeline: REST API → Pub/Sub → GCS → BigQuery — validating accuracy, completeness, and transformation correctness. Caught 15+ critical data loss and transformation defects pre-production, including schema mismatches, message deduplication failures, and late-delivery ordering issues. Built SQL-based BigQuery validation queries to reconcile source trade data against processed output — ensuring zero data loss in financial records. Coordinated with data engineers to define acceptance criteria for pipeline SLAs, error thresholds, and retry policies.
Banking Batch Automation — Nightly ETL & Settlement Jobs
March 1, 2024 – June 30, 2026
Validated 80+ Control-M job chains for Charles Schwab's nightly batch processing — covering trade settlement, account reconciliation, and regulatory reporting ETL workflows. Designed test scenarios for job dependency chains, trigger conditions, failure alert thresholds, and automated recovery sequences. Used Splunk to correlate batch job logs with downstream data — enabling rapid root cause analysis for settlement discrepancies and batch failures. Performed MSSQL post-batch validation — reconciling processed trade records against source data to ensure financial accuracy and completeness. Reduced post-batch defect detection time by 50% through proactive log monitoring and automated reconciliation checks.
REST API Automation Framework — Microservices Platform
January 1, 2024 – June 30, 2026
Designed and built an end-to-end API automation suite covering 12+ microservices handling trade orders, account management, and portfolio data for Charles Schwab's brokerage platform. Automated 60%+ of regression test cases — integrated into Jenkins CI/CD pipeline, cutting regression cycle time from 3 days to under 1 day. Covered API contract validation, service integration scenarios, error boundary testing, and cross-service data consistency checks across staging and production environments. Identified and reported 40+ critical API defects including payload mismatches, incorrect HTTP status codes, and broken contract validations before production release.
Google Cloud Professional Data Engineer
Google Cloud
January 1, 2027 – Present
Google Cloud Associate Cloud Engineer (GCP ACE)
Google Cloud
October 1, 2026 – Present
ISTQB Foundation Level
Unknown
September 1, 2026 – Present
The candidate scored 67% on the test, indicating a solid grasp of fundamental QA and testing concepts, but with room for improvement in more advanced or specific areas like multi-factor authentication automation or deeper Java/Selenium expertise.
Strengths
Cultural Fit Analysis
The candidate's experience across various project types (API, data pipeline, web UI, batch processing, event-driven messaging) within a single, large financial institution (Charles Schwab) demonstrates adaptability and a broad skill set. Their proactive pursuit of certifications (ISTQB, GCP ACE, GCP Professional Data Engineer) indicates a commitment to continuous learning and professional growth, which aligns well with a culture of innovation and excellence. The focus on reducing cycle times and improving quality also suggests a results-oriented mindset.
Soft Skills & Operational Fit
The candidate's resume highlights collaboration in Agile/Scrum environments, test planning, sprint estimation, and defect triage, indicating strong operational fit and teamwork capabilities. The use of AI tools like GitHub Copilot suggests an adaptive and efficient approach to problem-solving and development.
Limitations