Lead Software Engineer - Performance Engineering (Multiple openings) in Irving, TX

At U.S. Bank, we’re on a journey to do our best. Helping the customers and businesses we serve to make better and smarter financial decisions and enabling the communities we support to grow and succeed.  We believe it takes all of us to bring our shared ambition to life, and each person is unique in their potential. A career with U.S. Bank gives you a wide, ever-growing range of opportunities to discover what makes you thrive at every stage of your career. Try new things, learn new skills and discover what you excel at—all from Day One.

Job Description

U.S. Bank is seeking a full-time Lead Software Engineer - Performance Engineering (Multiple openings) in Irving, TX.

Essential Responsibilities:

Define software applications performance strategy and analyze performance results, tune applications and systems Key Performance Indicators (KPIs), and enhance performance of Consumer Banking Channel technologies, end-to-end technical solutions, improve resiliency and reliability of critical applications and L3 support for Mobile & Online banking applications. Specific duties include:

• Provide product support for U.S. Bank OLB/Mobile/TUX applications and conduct load tests to analyze application behavior for performance constraints using Jmeter and LoadRunner;
• Work with application development, network, database, and infrastructure specialists to identify and implement performance improvements and conduct performance testing of web-based applications, web service interfaces, mobile applications, back-end server components and Microservices using Jmeter and LoadRunner;
• Collaborate with developers to promote performance engineering best practices to catch performance earlier in the software development lifecycle;
• Monitor application performance, identify bottlenecks, and conduct root cause analysis utilizing AppDynamics, Kibana, Grafana and DataDog;
• Deploy applications on Kubernetes and utilizing Rancher to view and modify various parameters according to performance testing requirements;
• Deploy applications in Azure cloud environment, design and execute load tests in Azure environment, and provide performance recommendations;
• Design and execute load tests for Kafka based applications, and analyze Kafka producer and consumer performance metrics;
• Complete performance deep dive of JVM/CLR analysis to examine garbage collection, thread and heap dumps etc. using tools like Java visualVM;
• Leverage Gremlin for performing reliability engineering, chaos engineering, and circuit breaker testing;
• Utilize SeeTest for cross-platform mobile application and device testing using emulators and for profiling for applications;
• Utilize GitLab to manage repositories, and maintain Jenkins pipelines to automate build, test and deployment processes;
• Perform profiling and traceability of online transactions across multiple applications and create dashboards to provide transparency and latency between calls across applications; and
• Performance test and sizing for Sprint Boot based Microservices in Spring Cloud ecosystem as well as sizing parameters for Resilience4j configs.

Use the following tools and technologies: C, C#, Java, MS SQL, Oracle, MongoDB, Cassandra, jProfiler, Jmeter, LoadRunner, Gremlin, ELK (Elasticsearch-Logstash-Kibana), Kubernetes, Docker, Splunk, APIGEE, AppDynamics, JVM/CLR, Azure Cloud, Azure Kubernetes Service, (AKS), Azure Redis, Azure Vault, DataDog, Copilot, SeeTest, Kibana, REST, SOAP, Grafana, Kafka, Jenkins, Gitlab, Rancher, Java visualVM, Microservices, Spring Boot, Spring Cloud, Resilience4j. Multiple positions available.

Basic Qualifications:

This position requires a Bachelor’s degree or equivalent in Computer Science or Computer Engineering and 5 years (progressive, post-baccalaureate) experience in a software development occupation.

Required Skills/Experience:
 

Must also have 24 months of experience with each of the following: 1) Performance testing of web-based and mobile applications, web service interfaces (REST & SOAP), back-end server components, and Microservices using Jmeter and LoadRunner. 2) Monitor application performance, identify bottlenecks, and conduct root cause analysis utilizing APM tools including AppDynamics, Kibana, Grafana, and DataDog. 3) Design and execute load tests in Azure cloud environment, Azure Kubernetes, and Azure Redis. 4) Using C, C#, Java, MS SQL, Oracle, MongoDB, Cassandra, jProfiler, JMeter, Gremlin, ELK, Splunk, APIGEE, AppDynamics, Kafka, Jenkins, Gitlab, Kubernetes, Rancher, Java visualVM, Spring Boot, Spring Cloud, and Resilience4j. 5) Utilize SeeTest for mobile testing, multi-device testing, and profiling. 6) Leverage Gremlin for performing reliability engineering, chaos engineeri