EY is seeking a seasoned Site Reliability Engineering (SRE) Senior Consultant to drive IT modernization. This role involves acting as a technical advisor to develop and implement SRE principles and frameworks across enterprise IT. The focus is on transforming IT operations to enhance resilience, achieve predictability, optimize costs, and reduce IT risk.

You will be instrumental in assessing an organization's SRE maturity and crafting strategic roadmaps to elevate it. This is an opportunity to build a career with a global leader, contributing your unique perspective to a better working world.

Key responsibilities include defining Service Level Objectives (SLOs), Service Level Indicators (SLIs), and Service Level Agreements (SLAs) for products and services. You will engineer resilient design and implementation practices throughout the product lifecycle and develop robust observability solutions to monitor performance and SLA adherence.

Efforts will be directed towards engineering out manual processes (toil) through automation, including improvements in Continuous Integration and Continuous Deployment (CI/CD) pipelines. Additionally, you will optimize IT infrastructure and operational costs (FinOps) and conduct thorough reviews to simplify and improve deployed product architectures and inter-service dependencies.

A minimum of 15 years of experience in software product engineering principles, processes, and systems is required. Hands-on expertise in Java/J2EE, web servers (Apache Tomcat, IBM HTTP Server), application servers (Tomcat/WebSphere), and major RDBMS like Oracle is essential.

Proficiency in CI/CD tools (Azure DevOps, GitLab CI/CD, Jenkins) and Infrastructure as Code (IaC) tools (Terraform, AWS CloudFormation, Ansible) is expected. Experience with cloud technologies (AWS, Azure, GCP) and containerization/orchestration (Docker, Kubernetes, OpenShift) is crucial, alongside familiarity with reliability and observability tools (Azure App Insight, CloudWatch, Azure Monitor, Dynatrace, Splunk, ELK Stack).

Skills in defining NFRs and SLAs/SLOs/SLIs, understanding queuing models, and Linux (RHEL) performance monitoring are necessary. Experience with Web Services, SOA, ESB (DataPower), RESTful APIs, and application design patterns, including Microservices and Spring Boot, is also vital. Proficiency in Java runtimes, JVM tuning, application server performance tuning, and troubleshooting performance/scalability/availability issues is required. Mastery of collaborative development using Git, Jira, and Confluence is expected. Knowledge of AI/ML and Data Analytics is considered a plus.