Overview
We are seeking an experienced Performance Test Manager to lead and evolve our performance engineering capability. This role moves beyond traditional performance testing and focuses on embedding performance as a first-class engineering discipline across the SDLC.You will define strategy, build scalable frameworks, integrate performance into CI/CD pipelines, and leverage modern tooling such as k6, WebpageTest, and Datadog to ensure our systems are resilient, scalable, observable, and production-ready.You will partner closely with Engineering, Architecture, DevOps, and Product to drive ashift-left and shift-right performance culture.

Key Responsibilities

Performance Engineering Strategy
• Define and own the enterprise-wide performance engineering strategy aligned to business SLAs, SLOs, and architectural direction.
• Establish performance budgets, non-functional requirements (NFRs), and measurable success criteria early in the SDLC.
• Embed performance considerations into design reviews and architectural governance forums.
Modern Engineering & DevOps Enablement
• Integrate automated performance testing into CI/CD pipelines to enable continuous performance validation.
• Champion shift-left (early validation) and shift-right (production observability) practices.
• Enable performance gates within pipelines to prevent regressions before release.
• Promote Infrastructure-as-Code and ephemeral test environments for repeatable performance testing.
Tooling & Automation
• Define best practices for performance scripting using k6 with a strong emphasis on modular, reusable, and maintainable code.
• Drive automation-first principles across performance testing processes.
• Leverage WebpageTest for front-end performance optimization and Core Web Vitals analysis.
• Lead the strategic use of Datadog (APM, RUM, Synthetic Monitoring, dashboards, alerting) to connect test results with production telemetry.
Cloud-Native & Distributed Systems Performance
• Lead performance validation for microservices, APIs, event-driven systems, and containerized workloads.
• Validate scalability across Kubernetes clusters and cloud environments (AWS, Azure, GCP).
• Ensure resilience testing, autoscaling validation, and capacity modelling are embedded into release cycles.
Observability & Root Cause Analysis
• Establish observability standards aligned with performance diagnostics.
• Correlate performance test data with logs, traces, and metrics to identify systemic bottlenecks.
• Drive root cause analysis across application, infrastructure, database, and network layers.
Team Leadership & Capability Building
• Lead, mentor, and grow a high-performing performance engineering team.
• Foster a culture of engineering excellence, automation, and data-driven decision-making.
• Upskill QA and development teams in performance best practices.
Governance & Reporting
• Define KPIs for performance maturity and engineering effectiveness.
• Deliver executive-ready dashboards and reports highlighting risk, capacity trends, and scalability readiness.
• Provide capacity forecasts and scaling recommendations aligned with business growth projections.
Continuous Improvement
• Stay ahead of emerging trends in performance engineering, AI-driven observability, chaos engineering, and reliability practices.
• Continuously refine frameworks, tooling, and methodologies to improve speed, coverage, and insight.

Required Skills & Qualifications
Experience
• 10+ years of experience in software quality engineering, with strong specialization in performance engineering.
• 5+ years leading performance or non-functional testing teams in complex, distributed systems environments.
• Proven experience transforming traditional performance testing practices into modern engineering-led capabilities.
Technical Expertise
• Deep hands-on experience with k6 for performance scripting and automation.
• Strong expertise with Datadog (APM, metrics, tracing, dashboards, alerting) for performance analysis.
• Experience with WebpageTest and front-end performance optimization techniques.
• Strong understanding of microservices, APIs, containerization (Docker), orchestration (Kubernetes), and cloud-native architectures.
• Experience performance testing in AWS, Azure, or GCP environments.
• Solid understanding of scalability patterns, caching strategies, database performance tuning, and asynchronous/event-driven architectures.
Engineering & Automation
• Proficiency in JavaScript (k6), Python, or similar scripting languages.
• Experience integrating performance testing into CI/CD platforms (e.g., GitHub Actions, GitLab, Jenkins, Azure DevOps).
• Experience working with Infrastructure-as-Code (Terraform, CloudFormation) is desirable.
Leadership & Influence
• Strong stakeholder management and ability to influence architectural decisions.
• Ability to translate technical findings into business risk language.
• Excellent communication and executive reporting skills.