Role Overview
We are looking for an experienced Senior SDET to join our Quality Engineering team. The ideal candidate will have strong hands-on experience in test automation, API testing, UI automation, performance/load testing, distributed systems, Kafka, monitoring, and production-level debugging.
The role requires someone who can work across both API-based and event/stream-based services, understand complex system interactions, and independently investigate issues across services, logs, APIs, databases, messaging systems, and infrastructure.
The candidate should have a strong engineering mindset, excellent debugging skills, and the ability to identify quality risks early while working closely with Developers, Product Managers, Architects, and other stakeholders.
The focus is primarily on backend services, APIs, event-driven systems, UI automation, performance, observability, and end-to-end quality engineering.
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Design, develop, and maintain scalable and reliable automated test frameworks.
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Develop automated tests for both UI and backend/API services.
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Build and maintain API automation using tools such as REST Assured or equivalent.
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Develop reusable automation components and utilities.
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Integrate automated tests into CI/CD pipelines.
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Continuously improve automation coverage, reliability, and execution efficiency.
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Perform code reviews for automation and ensure adherence to engineering best practices.
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Functional testing
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Integration testing
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End-to-end testing
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Negative and boundary testing
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Contract/API validation
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Error handling and resilience scenarios
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Validate interactions between multiple backend services.
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Test REST-based microservices and service-to-service communication.
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Analyze API requests/responses and identify issues across upstream and downstream dependencies.
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Work with event-driven and stream-based architectures.
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Design and execute test scenarios for Kafka-based services.
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Validate message production, consumption, processing, ordering, duplication, retries, and failure scenarios.
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Verify end-to-end data flow across producers, Kafka topics, consumers, and downstream services.
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Troubleshoot issues involving asynchronous processing and eventual consistency.
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Validate both API-driven and event-driven business flows.
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Develop and maintain robust UI automation for web applications.
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Use frameworks such as Selenium, Playwright, or equivalent.
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Create reusable page/component-level automation.
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Integrate UI automation into CI/CD pipelines.
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Ensure critical end-to-end business journeys are covered through automation.
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Design and execute load, stress, scalability, endurance, and performance tests.
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Analyze system behavior under different traffic, concurrency, and throughput levels.
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Identify performance bottlenecks across APIs, services, Kafka, databases, and infrastructure.
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Analyze metrics such as RPS, latency, throughput, error rate, CPU, memory, connection pools, and resource utilization.
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Work closely with developers and architects to identify and resolve performance bottlenecks.
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Contribute to performance benchmarking, capacity planning, and scalability validation.
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Use monitoring and observability platforms such as Grafana and Dynatrace to analyze system health and performance.
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Monitor application and infrastructure metrics during functional and performance testing.
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Analyze dashboards, service metrics, traces, and alerts to identify abnormal system behavior.
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Correlate application behavior with infrastructure and service-level metrics.
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Use monitoring data to support defect investigation and root-cause analysis.
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Demonstrate strong hands-on debugging skills across distributed systems.
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Application logs
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API requests/responses
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Kafka messages and topics
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Database records
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Monitoring dashboards
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Distributed traces
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Service metrics
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Perform end-to-end troubleshooting across multiple services and dependencies.
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Distinguish between application, infrastructure, data, configuration, and environment-related issues.
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Drive issues towards root-cause identification, rather than only reporting symptoms.
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Collaborate with developers and other engineering teams to resolve complex production and non-production issues.
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Understand business requirements and technical architecture to derive comprehensive test scenarios.
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Create and review test cases covering functional, business, integration, negative, and edge-case scenarios.
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Identify gaps and quality risks during requirement and design discussions.
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Ensure adequate coverage across both business workflows and technical integrations.
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Collaborate with other teams to review test scenarios and achieve maximum end-to-end coverage.
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Take end-to-end ownership of quality for assigned features and services.
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Define test strategy, test scope, automation approach, and quality gates.
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Proactively identify risks early in the development lifecycle.
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Drive shift-left testing and continuous quality practices.
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Mentor other QA/SDET engineers on automation, debugging, performance testing, and quality engineering practices.
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Contribute to improvements in testing frameworks, processes, tooling, and engineering practices.
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5+ years of experience in Software Testing, SDET, or Quality Engineering.
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Strong programming experience in Java, Python, or equivalent.
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Strong hands-on experience in API automation using REST Assured or equivalent.
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Strong experience in UI automation using Selenium, Playwright, or equivalent.
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Strong understanding of REST APIs, HTTP, JSON, authentication, and microservices.
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Hands-on experience with Kafka and event/stream-based architectures.
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Strong experience in functional, integration, API, and end-to-end testing.
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Hands-on experience with load/performance testing.
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Experience with Grafana, Dynatrace, or similar monitoring/observability tools.
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Strong ability to analyze application logs and distributed system failures.
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Strong debugging and root-cause analysis skills.
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Good understanding of SQL and/or NoSQL databases.
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Experience with Git and CI/CD pipelines.
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Good understanding of Agile/Scrum methodologies.
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Experience testing highly scalable and distributed systems.
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Experience with performance testing tools such as JMeter, Gatling, Locust, or equivalent.
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Experience with AWS or other cloud platforms.
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Experience with Docker/Kubernetes.
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Experience with OpenSearch/ELK or similar log-analysis platforms.
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Experience with distributed tracing and observability.
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Experience with event-driven/microservices architectures.
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Experience with contract testing and service virtualization.
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Experience in designing or modernizing automation frameworks.
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Exposure to AI-assisted testing or AI Quality Engineering.
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Strong debugging and analytical skills
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Strong automation and coding skills
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End-to-end ownership
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Ability to understand complex distributed systems
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Ability to work across API and stream/event-based services
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Strong problem-solving and root-cause analysis skills
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Ability to interpret logs and monitoring data independently
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Strong collaboration and communication skills
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Ability to challenge requirements and designs constructively from a quality perspective
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Ability to mentor and guide other engineers
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Strong focus on automation, scalability, reliability, and continuous improvement
