Senior Performance Engineer

Location: Plano, TX (5 days on-site) 12 months About The Role Sands is seeking an experienced Senior Performance Engineer to join its enterprise applications team.

The successful candidate will lead performance engineering for a business-critical enterprise application suite in preparation for its go-live at a Sands property.

The role is responsible for establishing performance baselines, validating that the application scales to production traffic volumes, and confirming that it operates within its sized capacity on production hardware.

The application is hosted on Red Hat OpenShift running on on-premises servers, across both non-production and production environments.

As this infrastructure has fixed capacity, and additional hardware requires significant procurement lead time, accurate measurement and forecasting are central to the position.

The Senior Performance Engineer will work independently, conducting their own research and analysis, and will collaborate closely with development, database, platform engineering and vendor teams.

Key Responsibilities

• Establish, measure and maintain performance baselines for each release across API, service and user-interface scenarios, weighted in proportion to actual usage.
• Develop workload models, including transaction volumes, concurrent users, transactions per second and test durations, derived from production traffic data and agreed with business stakeholders and vendors.
• Design, develop and maintain performance test scripts using JMeter, Artillery and Playwright, reusing existing test assets where appropriate.
• Execute load and endurance tests throughout each release cycle in a dedicated performance environment.
• Validate application scalability at and beyond production traffic volumes, assess utilization of CPU, memory, database and storage capacity, and report remaining headroom and capacity limits in time to inform hardware planning.
• Analyze test results against baselines, identify regressions promptly, and determine root causes using platform, database and application metrics.
• Partner with developers, database administrators and platform engineers to resolve performance issues, including query optimization, resource configuration, runtime tuning and scaling.
• Prepare performance reports and present findings and recommendations to support formal release approval.
• Work with platform engineering to ensure the performance environment remains representative of production and is managed through GitOps practices.
• Identify and coordinate dependencies required for testing, including interface inventories, test accounts, test data and integration stubs.
• Prepare and maintain production-scale, anonymized test data sets.

Qualifications And Experience

• Minimum of seven years of experience in performance engineering or performance testing of enterprise web applications, including leading performance testing for major releases or system go-lives and presenting capacity findings to senior leadership.
• Demonstrated ability to work independently, including researching unfamiliar systems, forming and testing hypotheses, and drawing sound conclusions with minimal direction.
• Experience in capacity planning for fixed, on-premises infrastructure, including sizing workloads to available hardware, extrapolating results from non-production to production environments, and forecasting future capacity requirements.
• Hands-on scripting experience with JMeter and at least one additional load testing tool such as Artillery, k6, Gatling or Locust.
• Experience with user-interface performance testing using Playwright or a comparable browser automation tool.
• Strong understanding of load and endurance testing, workload modeling based on production traffic, and percentile-based performance analysis.
• Experience testing REST APIs and service-to-service communication in distributed systems.
• Hands-on expertise with Kubernetes, including configuring resource requests and limits, horizontal and vertical scaling, node scheduling, and analyzing pod, node and cluster-level metrics and logs to diagnose performance issues.
• Proficiency with Kubernetes tooling, including kubectl and the OpenShift CLI (oc), Helm and Kustomize, for deploying, inspecting and troubleshooting workloads.
• Proficiency in interpreting monitoring data from tools such as Prometheus and Grafana to identify bottlenecks across application, database and infrastructure layers.
• Strong SQL skills and familiarity with relational database performance, preferably PostgreSQL.
• Proficiency in at least one programming or scripting language, such as Python, JavaScript or Java.
• Excellent written and verbal communication skills, with the ability to present technical findings to both technical and business audiences.

Preferred Qualifications

• Experience with on-premises Red Hat OpenShift deployments, particularly on bare-metal infrastructure.
• Familiarity with GitOps practices and tools such as Argo CD or OpenShift GitOps.
• Experience in Java and JVM performance tuning, including memory management, garbage collection and thread pool configuration.
• Experience with application performance monitoring (APM) tools for distributed tracing.
• Experience in regulated industries such as gaming, hospitality or financial services.
• Knowledge of enterprise storage performance, including block and network file storage.
• Experience establishing performance testing within a release process that includes formal approval gates.

Technical Environment The role works with JMeter, Artillery and Playwright for test execution; Red Hat OpenShift on bare-metal servers in Sands datacenters, across non-production and production environments; a dedicated performance environment hosting the full application stack; GitOps-based deployment; OpenShift monitoring with Prometheus and Grafana; and PostgreSQL databases.

Key Outcomes

Within the first three months, the successful candidate will be expected to:

• Define and implement baseline test scenarios across API, service and user-interface layers.
• Deliver a capacity assessment of the application on production hardware at production traffic volumes, including available headroom and capacity limits.
• Establish regular load testing within each release cycle, with results published after every run.
• Implement scheduled endurance testing with no unexplained performance degradation.
• Identify and resolve performance regressions before releases are promoted.