Leads and performs performance testing, performance engineering, and scalability analysis for enterprise applications, cloud-native platforms, data warehouse solutions, and data lake ecosystems. Defines performance test strategies, designs realistic workload models, develops and executes performance tests using tools such as NeoLoad, and analyzes system behavior across application, database, infrastructure, and cloud layers. Collaborates with product, development, architecture, infrastructure, and operations teams to identify performance risks, establish baselines, validate non-functional requirements, and provide actionable recommendations to improve throughput, reliability, resiliency, and user experience.

ESSENTIAL FUNCTIONS:
Develop and execute end-to-end performance test strategies for enterprise applications, AWS-native applications, APIs, microservices, data warehouse platforms, and data lake pipelines. Define performance objectives, workload models, test data needs, test schedules, and entry and exit criteria. Design and execute load, stress, endurance, scalability, resiliency, and capacity tests using NeoLoad and other approved enterprise performance testing tools. Automate performance test execution within CI/CD pipelines to support repeatable validation, early performance feedback, and release readiness.
Analyze performance test results across application, database, middleware, network, cloud, and infrastructure layers. Monitor and evaluate key metrics such as response time, throughput, transaction volume, CPU, memory, I/O, queue depth, latency, error rates, auto-scaling behavior, and system recovery. Identify bottlenecks and performance risks, compile findings, and communicate clear recommendations to technology, product, and leadership stakeholders.
Support performance engineering for cloud modernization, data platform migrations, and high-volume processing solutions. Validate performance and scalability of AWS services, cloud-native architectures, containerized workloads, data ingestion jobs, ETL/ELT pipelines, PostgreSQL and other database platforms, data warehouse workloads, and data lake integrations. Partner with architecture and engineering teams to recommend tuning opportunities, capacity improvements, automation enhancements, and long-term performance solutions.
Provide technical leadership for performance testing engagements supporting critical, high-visibility applications and platforms. Lead defect triage and root-cause analysis for performance issues, support production incident analysis where performance is a contributing factor, and help establish performance baselines, dashboards, and reporting standards. Mentor team members on performance testing best practices, NeoLoad scripting and execution, cloud observability, test automation integration, CI/CD performance test automation, and continuous performance testing within delivery pipelines.

Qualifications
To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable
accommodations may be made to enable individuals with disabilities to perform the essential functions.

Education Level: Bachelor's Degree
Education Details: Information Technology or Computer Science

Experience: 5 years experience in performance testing, performance engineering, or quality engineering for enterprise applications, including hands-on experience with workload modeling, performance test design, test execution, monitoring, bottleneck analysis, and results reporting. Experience with NeoLoad or similar performance testing tools, CI/CD performance test automation, cloud platforms such as AWS, database performance validation, and large-scale data warehouse or data lake environments is preferred.

In Lieu of Education
In lieu of a Bachelor's degree, an additional 4 years of relevant work experience is required in addition to the required work experience.

Preferred Qualifications
Knowledge, Skills and Abilities (KSAs)
Ability to communicate technical requirements to all levels of expertise., Advanced
Proficient in establishing and maintaining good working relationships., Advanced
Knowledge and understanding of performance testing lifecycle, SDLC, Agile delivery, and non-functional requirements validation., Advanced
Proficient with integrating performance testing into complex enterprise systems, cloud-native applications, APIs, microservices, data warehouse platforms, and data lake pipelines., Advanced
Knowledge of scripting, programming, or query languages used in performance testing and analysis, such as JavaScript, Java, Groovy, Python, SQL, or shell scripting., Proficient
Excellent communication skills both written and verbal., Advanced
Knowledge of cloud technologies with emphasis on AWS-native applications, cloud scalability, auto-scaling behavior, monitoring, observability, resiliency, and capacity validation., Advanced
Knowledge of database and data platform technologies, including SQL, Oracle, PostgreSQL, MongoDB, data warehouse platforms, data lake environments, ETL/ELT pipelines, and large-scale data ingestion performance., Advanced
Knowledge of performance engineering best practices, cloud performance patterns, agile methodologies, observability, CI/CD pipelines, automated performance test gates, and continuous performance testing practices., Advanced
Knowledge of test automation practices, test data management, workload modeling, API testing, service virtualization, CI/CD performance test automation, and integration of performance tests into automated delivery pipelines., Advanced
Strong experience with NeoLoad or comparable performance testing tools, cloud monitoring tools, deployment/continuous integration/continuous testing/continuous delivery processes, CI/CD performance test automation, and performance reporting dashboards., Advanced
Knowledge of Code quality and promotion practices, Advanced