Senior Performance Engineer

Dataart Technologies; Bengaluru; On-site; INR 900,000 - 1,600,000; Full time

Job summary

Dataart Technologies is seeking a Senior Performance Engineer in Bengaluru to lead end-to-end performance testing across multiple applications. You will define requirements with product owners, build and maintain JMeter scripts, and run comprehensive load/stress tests in containerized environments using AWS/Azure.

You will own the test framework, integrate with GitHub Actions, and develop observability dashboards in CloudWatch, Grafana, and New Relic.

Qualifications

• Senior-level performance engineering across multiple applications.
• Strong JMeter scripting and workload modelling experience.
• Experience maintaining scripts and test data in GitHub.
• Hands-on experience with load, stress, spike, and soak testing.
• Experience with CI/CD integration of performance tests using GitHub Actions or equivalent tools.
• Experience validating autoscaling, caching, load balancing, and failover on containerized workloads.
• Experience with an APM or observability platform such as CloudWatch, Grafana, New Relic, or similar.
• Experience validating golden signals SLI s and SLOs.
• Strong root cause analysis and tuning skills across application, API, database, network, and container layers.
• Experience with front-end performance testing alongside server-side testing.
• Experience with chaos and fault injection testing.
• Working knowledge of AWS and Azure
• Working knowledge of Docker and Kubernetes
• Experience with defect tracking and reporting in Jira and Confluence
• Ability to present findings to engineering and business stakeholders
• Experience working in Agile teams
• Experience working in DevOps environments
• Ability to communicate clearly with developers, product, and delivery teams

Responsibilities

• Own performance testing delivery across multiple applications from requirements through execution analysis and reporting.
• Define performance requirements with product owners and developers.
• Validate environment readiness before each test cycle.
• Build and maintain JMeter scripts workload models and test data in GitHub.
• Use similar tools such as K6 Gatling NeoLoad or LoadRunner when applicable.
• Own the performance test framework and its CI CD pipelines on GitHub Actions or an equivalent tool.
• Run load stress spike and soak tests on containerized workloads.
• Validate autoscaling caching load balancing and failover during performance testing.
• Test front end performance alongside server side performance.
• Build dashboards in CloudWatch and Grafana covering RUM APM infrastructure logs and traces.
• Use Prometheus or OpenTelemetry data in observability dashboards.
• Correlate New Relic and Google Analytics data with test runs.
• Validate golden signals SLIs and SLOs.
• Use observability data to pinpoint bottlenecks across application API database network and container layers.
• Recommend tuning and scaling changes and validate them with repeat tests.
• Run chaos and fault injection tests on AWS and Azure using native tooling.
• Contribute reusable scripts dashboards and runbooks that explain each application's resiliency setup.
• Track performance defects to closure in Jira.
• Coordinate with developers and product teams on defect priority and impact.
• Deliver test summary reports in Confluence with release readiness evidence for engineering teams and leadership.
• Use AWS and Azure for deployment secrets database services and performance test infrastructure

Skills

Performance engineering

JMeter scripting

GitHub workflows

CI/CD

Observability

Root cause analysis

Agile

DevOps

Stakeholder communication

Tools

CloudWatch

Grafana

New Relic

Jira

Confluence

K6/Gatling/NeoLoad/LoadRunner

Docker

Kubernetes

Job description

Responsibilities

• Own performance testing delivery across multiple applications from requirements through execution analysis and reporting
• Define performance requirements with product owners and developers
• Validate environment readiness before each test cycle
• Build and maintain JMeter scripts workload models and test data in GitHub
• Use similar tools such as K6 Gatling NeoLoad or LoadRunner when applicable
• Own the performance test framework and its CI CD pipelines on GitHub Actions or an equivalent tool
• Run load stress spike and soak tests on containerized workloads
• Validate autoscaling caching load balancing and failover during performance testing
• Test front end performance alongside server side performance
• Build dashboards in CloudWatch and Grafana covering RUM APM infrastructure logs and traces
• Use Prometheus or OpenTelemetry data in observability dashboards
• Correlate New Relic and Google Analytics data with test runs
• Validate golden signals SLIs and SLOs
• Use observability data to pinpoint bottlenecks across application API database network and container layers
• Recommend tuning and scaling changes and validate them with repeat tests
• Run chaos and fault injection tests on AWS and Azure using native tooling
• Contribute reusable scripts dashboards and runbooks that explain each application's resiliency setup
• Track performance defects to closure in Jira
• Coordinate with developers and product teams on defect priority and impact
• Deliver test summary reports in Confluence with release readiness evidence for engineering teams and leadership
• Use AWS and Azure for deployment secrets database services and performance test infrastructure

Requirements

• Senior-level performance engineering experience across multiple applications
• Strong JMeter scripting and workload modelling experience
• Experience maintaining scripts and test data in GitHub
• Hands-on experience with load, stress, spike, and soak testing
• Experience with CI CD integration of performance tests using GitHub Actions or equivalent tools
• Experience validating autoscaling, caching, load balancing, and failover on containerized workloads
• Experience with an APM or observability platform such as CloudWatch, Grafana, New Relic, or similar
• Experience validating golden signals SLIs and SLOs
• Strong root cause analysis and tuning skills across application, API, database, network, and container layers
• Experience with front-end performance testing alongside server-side testing
• Experience with chaos and fault injection testing
• Working knowledge of AWS and Azure
• Working knowledge of Docker and Kubernetes
• Working knowledge of distributed systems and resiliency patterns
• Experience with defect tracking and reporting in Jira and Confluence
• Ability to present findings to engineering and business stakeholders
• Experience working in Agile teams
• Experience working in DevOps environments
• Ability to communicate clearly with developers, product, and delivery teams

Nice to have

• Hands-on use of AI coding assistants such as GitHub Copilot Claude Code Cursor Codex or equivalent to write and generate load test scripts
• Familiarity with GenAI LLMs and agentic workflows for maintaining performance scripts
• Familiarity with RAG and MCP concepts for QE tooling and for generating test data for load scenarios
• Experience with service virtualization using WireMock or an equivalent tool
• Experience with Tableau or an equivalent reporting tool
• Experience with Azure Monitor