Poojitha A S

About Poojitha A S

As a Senior SRE / DevOps Engineer with 10+ years across AWS, Azure, Kubernetes, Terraform, and CI/CD, I bridge engineering excellence with business reliability.I’ve led cloud migrations for 200+ applications, reduced infrastructure costs by ~30%, and improved release velocity by ~40%. I’ve designed self-healing Kubernetes clusters with automated scaling and failover (cutting downtime by ~90%), and implemented observability + incident-response frameworks (Dynatrace, Grafana, Prometheus) that shortened MTTR by ~50%.Beyond my engineering work at Amadeus and CGI, I’m a DevOps community builder and content creator:1M+ post impressions and professionals reached in under a yearContent focused on Terraform, Kubernetes, and practical DevOps workflowsActive in meetups and conferences, mentoring engineers on cloud-native patterns and career growthI care about making complex cloud practices simple, reliable, and scalable for real-world teams. My leadership style blends empathy, structure, and execution — from mentoring women in tech at C3 Women to helping professionals with career transitions and LinkedIn optimization.What I’m interested in nowSenior / Staff / Principal SRE or DevOps roles (multi-cloud, large-scale systems)Speaking, panels, and workshops in the DevOps & cloud-native spaceCollaborations around content, community, or mentorshipLet’s connectEmail: p••••••••@gmail.comBook a 30‑minute Google Meet with me: https://calendly.com/poojithaas/new-meeting

Experience

1. Site Reliability Engineer

   Tekhubinc

   Sep 2024 — Present · Plano, TX, US

   Built scalable data processing pipelines using Databricks and Apache Spark, ingesting and transforming large datasets stored in Amazon S3 for analytics and ML workloads.• Deployed containerized data and ML services on Amazon EKS, enabling scalable microservices that interact with Databricks pipelines and downstream applications.• Automated infrastructure provisioning using Terraform and Kubernetes manifests, integrating Databricks workloads with EKS-based services and CI/CD pipelines.• Improved reliability and performance by implementing monitoring and observability across Databricks jobs and EKS clusters using CloudWatch, Prometheus, and centralized loggi