Sep 2023 – Dec 2023 · 3 mos · Rochester, New York Metropolitan Area · Remote

• 1. Worked on Standardization of tags across Azure cloud to build better observability of azure resources.
• 2. Created dashboards for resource utilization using azure workbooks for virtual machines, blob storage and SQL servers.
• 3. Dashboards helped in getting more insights about stale resources and take actions accordingly to reduce cloud cost.
• 4. Using above workbook for dev account we identified ~40% of resources in the account being stale.

May 2022 – Aug 2022 · 3 mos · Seattle, Washington, United States

• 1. Designed services responsible to verify the underlying isolated compute environment & return the encrypted data encryption key. This made sure that enclaves are trusted and authorized code is running in it.
• 2. Attestation Validation : This service is responsible to verify the enclaves by verifying the attestation document generated from AWS nitro enclaves by using X509 certificate chain, PCR’s & signature present in the document.
• 3. Key Storage Service: Responsible for fetching the data encryption key for the passed study id from DynamoDB.
• 4. Dek Encryption : Responsible to encrypt the fetched DEK using the RSA algorithm.
• 5. TEE Coordinator : This service is responsible for coordinating the entire workflow using AWS lambda & APIGateways.

Aug 2020 – Jul 2021 · 11 mos · Mumbai, Maharashtra, India

• 1. Design Predictive scaling tool where Infrastructure gets scaled automatically based on Predicted Concurrency. This helped us in saving around 15% of our AWS cost.
• 2. Optimised scaling time by ~58% for peak Concurrency of 7Million Users.
• 3. Wrote Deployment Job which help Release team increase their productivity. This job support creation of new stack, routing of traffic, perform error analysis, rollback incase of failure.
• 4. Reduce the AWS rate Limiting by managing inventory in house for Auto Scaling Group, Load Balancer and Route53 using RDS, Lambda and Eventbridge.

Jul 2018 – Aug 2020 · 2 yrs 1 mo · Mumbai Area, India

• 1. Deployed Big Data Spark pipelines on :
• A. Kubernetes in production landscape ; Scheduled 21 pipelines in a batch of 3 using Multi-Processing; Setup Prometheus & Grafana for Monitoring and Scaling k8s cluster as per the load ; Set up CI/CD using Azure Devops where Spark Docker images are pushed to Azure Container Registry.
• B. Databricks : Improved the performance of above pipelines by 23% by deploying on Databricks Cluster; Migrated Solution from k8s to Databricks; Use Azure Data Factory for batch scheduling of pipelines.
• 2.. Automated the infrastructure deployment using Terraform on AWS.
• 3 . PaQt : Portal to train College graduates. Set Up the Authentication and Authorisation in application using AWS Cognito and AWS Lambda.

Apr 2017 – Jul 2017 · 3 mos · Mumbai Area, India

• 1. Deployed model on AWS using Django where end user hits REST API to get results generated by model.
• 2. Endpoint was secured with user Authentication Token and SSL.