♦ Created a Sentiment Analysis Solution to help brands get detailed insights regarding customer sentiment and perception through online engagements across sources like Twitter, YouTube, and Google Reviews♦ Utilized Google Natural Language, BERT and Big Query to create a Sentiment analysis pipeline for customer product sentiment ♦ Leveraged Google Data studio to create analytics and visualize results of multiple machine learning models. Data was visualized as sentiment over time, sentiment variation by geographic location, and word clouds for common adjectives♦ Technologies: Python, Google Natural Language API, Big Query, Vertex Ai, Data Studio, TensorFlow, GloVe, Keras

AWS/GCP/AZURE♦ Cost Management - Designed and implemented internal website to aggregate and report on billing across providers , reporting by team and workload. Automated tagging new resources.♦ Cost Optimization - Automated server startup and shutdown by tagging workloads with serveless technology.♦ Least Privileged Access - Created centralized self service website for requesting, granting and managing RBAC♦ Security - Automated management of Security groups(AWs)/Firewall rules, GCP/ Azure, by creating a self service ticketing system♦ Security Monitoring - Serverless monitoring of security rules and alerting in realtime on email & slackPerformed cost comparison between EC2, Fargate and EKS, for a new project to cost optimize and chose EKS balance ease of use and cost♦ Containerized and deployed multiple Spring Boot/ Vert.x applications on EKS with terraform and helm charts♦ Performance analysis of AWS glue/Spark vs Hadoop to process and optimize indexes on 50GB of data. Selected AWS Glue based on detailed analysis of metrics♦ Designed and built User Recommendation System for Twitter users based on interactions, similarity in interests and topics as a Solutions Architect.♦ Technologies : Python, boto3, Django, ReactJs, EC2, Compute Engine, Cloud Function, Cloud Watch, Cloud Trail, VPC, Lambda, Google Cloud, Spring Boot, Terraform, EKS, Fargate, AWS Glue, HadoopCloud Migration On-Prem and AZURE to AWS♦ Leveraged Cloud Endure to migrate PowerBI & Talend servers on-prem to AWSMigrated 5 postGres DB Azure to AWS, using AWS DMS♦ Technologies: CloudEndure, AWS DMS, DynamoDB, RDS, PostgreSQL, AWS Glue, AWS DataPipeline, Docker, Kubernetes