Job Description: Performance Load Test Architect / Lead
Middletown,PA
Remote

Key Responsibilities

Strategic Planning & Governance

• Define and own the overall performance engineering strategy for the enterprise modernization initiative.

• Establish enterprise performance testing standards, governance frameworks, methodologies, and best practices.

• Develop realistic workload models based on historical production metrics and projected business growth.

• Establish non-functional requirements (NFRs), Service Level Objectives (SLOs), Service Level Agreements (SLAs), and performance acceptance criteria.

• Lead performance planning across all project phases: Solution Confirmation, PI Planning, SIT, UAT, Go-Live, and Hypercare.

• Review end-to-end solution architectures early in the SDLC to identify scalability risks, infrastructure constraints, and potential bottlenecks.

• Provide technical leadership for enterprise capacity planning and infrastructure sizing recommendations.

Performance Engineering Leadership & Execution

• Lead performance testing across a complex technology ecosystem, including:

  • SAP BRIM, SAP Convergent Mediation (CM), SAP S/4HANA, and SAP Datasphere

  • Dynamics CRM / Customer Engagement platforms

  • Enterprise Middleware, REST/SOAP APIs, and event-driven architectures

  • High-volume batch processing systems

  • Customer web portals and mobile applications

  • IVR and automated chatbot platforms

• Formulate enterprise load profiles covering concurrent user volumes, transaction throughput, billing cycles, payment processing, transaction ingestion, financial reconciliation, and customer service operations.

• Review, guide, and sign off on performance test plans, scripts, workload models, and execution schedules prepared by performance engineers and analysts.

Architecture, Monitoring & Analysis

• Architect and implement an end-to-end monitoring and observability strategy across applications, middleware, SAP, databases, and cloud infrastructure.

• Analyze system metrics, including response times, throughput, JVM metrics, database locks/queries, message queues, API latencies, and resource utilization.

• Lead cross-functional root-cause analysis (RCA) alongside development, infrastructure, middleware, functional ERP, and third-party vendor teams.

• Provide actionable tuning recommendations for application runtimes, database queries/indexes, infrastructure auto-scaling, and system configurations.

• Validate and certify overall system readiness ahead of production deployments.

Tooling & Automation

• Lead the implementation, administration, and scaling of NeoLoad as the enterprise performance testing platform.

• Design modular, reusable scripting frameworks and standardized load generation patterns.

• Integrate automated performance regression test suites into major deployment pipelines.

• Develop executive-ready performance dashboards, KPIs, and release sign-off reports.

Collaboration & Stakeholder Management

• Present performance findings, risk assessments, bottlenecks, and mitigation plans to technical leads, steering committees, and executive leadership.

• Author and maintain comprehensive program documentation, including architecture diagrams, test strategies, impact analyses, lessons learned, and standard operating procedures.

• Ensure full alignment with organizational IT standards, security frameworks, and governance policies.

Required Qualifications & Experience

• 12+ years of progressive IT experience.

• 8+ years of dedicated experience in enterprise performance engineering and load testing.

• 5+ years in a technical leadership or architectural capacity driving enterprise performance initiatives.

• Expert-level proficiency in NeoLoad (scripting, scenario modeling, infrastructure, and reporting).

• Proven track record architecting performance testing solutions for large-scale, high-throughput enterprise platforms.

• Hands-on performance testing experience across SAP ecosystems (BRIM, S/4HANA, Convergent Mediation, Datasphere), CRM platforms, APIs, and integration middleware.

• Deep expertise in building data-driven workload models from production logs and historical transaction volumes.

• Strong subject-matter expertise in:

  • Capacity planning and infrastructure sizing

  • High-availability, failover, spike, stress, and endurance testing

  • Batch job optimization and asynchronous messaging

  • Cloud and hybrid infrastructure performance diagnostics