Performance Engineer at Salesforce enhancing Marketing Cloud experiences. Collaborating on performance metrics and optimizing frontend/backend systems for scalability.
Responsibilities
Ensure high-performing and scalable Marketing experiences across both frontend and backend systems as a Performance Engineer for Marketing Cloud.
Collaborate with engineering teams on performance test plan design and execution, implementing meaningful metrics, and building dashboards reflecting real-world customer usage.
Develop and maintain automated benchmarks and performance regression reports to track improvements and identify issues across releases.
Troubleshoot performance bottlenecks in frontend (browser/UI), backend (APIs/services), and data layers, providing actionable insights and partnering with developers for resolution.
Conduct deep-dive diagnostics using various tools and profiling techniques to analyze system behavior, latency, and throughput.
Contribute to the development of internal performance tools, CI/CD integrations, and frameworks, including leveraging AI agents for enhanced automation, detection, and triage.
Document performance defects clearly when regressions occur and work with cross-functional teams to resolve them.
Promote the adoption of performance best practices by integrating performance considerations early in the development lifecycle.
Requirements
6+ years of experience in performance engineering, systems optimization, or backend/frontend diagnostics.
Strong understanding of React, JavaScript, microservices, and distributed systems in cloud environments.
Proficiency in performance fundamentals: Frontend: Browser rendering, JavaScript optimization, and network analysis.
Backend: SQL performance analysis, query tuning, indexing, and caching strategies.
Hands-on experience with tools such as JMeter, Gatling, Chrome DevTools, YourKit, and Java Flight Recorder.
Scripting expertise in Python, Bash, or Node.js, with the ability to create automation tools and pipelines.
Familiarity with AI-driven tools or agents for performance monitoring, log analysis, or auto-diagnosis.
Ability to interpret performance data, pinpoint root causes, and clearly communicate findings.
Knowledge of data concepts related to relational databases and NoSQL stores.
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