Join our dynamic Engineering team as a Consultant, specializing in GCP Site Reliability Engineering (SRE). You will be instrumental in managing and scaling critical production systems on Google Cloud Platform (GCP), focusing on enhancing reliability, implementing automation, and driving operational excellence. The ultimate goal is to elevate system availability from 4 Nines to 5 Nines through innovative engineering solutions. This role demands profound technical acumen in cloud-native technologies, Kubernetes, infrastructure automation, and Linux administration, coupled with exceptional troubleshooting skills for complex distributed systems.

Take ownership of end-to-end production system reliability, availability, scalability, cost, and performance. Drive significant improvements in MTTR and MTTA through automation and process enhancements. Actively participate in 24x7 on-call rotations, manage high-severity incidents, and contribute to knowledge sharing to prevent future occurrences. Define and manage key reliability metrics like SLIs, SLOs, SLAs, and Error Budgets in close collaboration with engineering teams. Design, deploy, and maintain infrastructure on GCP, utilizing services like GKE, Compute, VPC, IAM, and Load Balancers. Implement and manage infrastructure as code using Terraform. Troubleshoot and manage containerized workloads on Kubernetes (GKE), resolving issues related to pods, nodes, networking, and storage. Build and maintain CI/CD pipelines using Jenkins and manage version control via GitHub. Develop automation scripts in Python and Shell to reduce manual tasks and enhance efficiency. Implement and manage monitoring tools like Dynatrace and Grafana, leveraging logs, metrics, and traces for proactive problem identification.

A Bachelor's degree in Engineering is required, along with 5-8 years of progressive experience in SRE, DevOps, or Cloud Engineering. Proven hands-on experience managing production-grade systems in 24x7 environments is essential. Demonstrated strong expertise in GCP (including GKE, VPC, IAM, Load Balancing, KMS, logs, metrics, BigQuery, Pub/Sub) and deep expertise in Kubernetes (GKE) and Docker with robust troubleshooting capabilities are critical. You should have strong hands-on experience with Terraform for infrastructure as code and practical experience with Jenkins (pipeline-based) and GitHub for CI/CD and version control. Proficiency in Python (preferred) and Shell scripting is required, along with a working knowledge of Java and/or Golang applications. A solid understanding of Linux fundamentals, TCP/IP networking, SLIs, SLOs, SLAs, and Error Budgets is necessary. Experience in improving MTTR and MTTA, along with extensive experience in incident management, is highly valued. Excellent analytical and troubleshooting skills, strong communication abilities, and stakeholder management are key. The ideal candidate is ownership-driven, proactive, and comfortable working in high-pressure production settings, with experience in high-scale distributed systems and an understanding of banking/financial domain practices.