Responsible for cost reduction for entire Apple Cloud infrastructure (AWS, GCP, ALI).

Implemented cost optimization strategies by identifying idle instances, right-sizing resources, and migrating workloads to cost-effective Graviton instances.

Led initiatives to upgrade storage volumes from GP2 to GP3, reducing costs and improving performance for database workloads.

Developed a Python-based solution using PostgreSQL and SQLAlchemy to orchestrate seamless table creation, updates, and deletions, using mix-ins to encapsulate reusable behaviors, enhancing code modularity and scalability within the application's data management system.

Automated infrastructure provisioning and configuration management using Terraform and Ansible, enabling consistent deployment and efficient resource utilization.

Developed custom scripts and tools in Python to analyze cost data, identify cost-saving opportunities, and generate optimization recommendations.

Conducted performance analysis and tuning exercises to optimize resource utilization, enhance application performance, and reduce infrastructure costs.

Collaborated with cross-functional teams to establish cost optimization best practices, monitor cost trends, and drive continuous improvement initiatives.

Created AWS Lambdas using Terraform scripts as part of the CI/CD process.

Gathered infrastructure usage data from Cloudability and stored it in a PostgreSQL database to facilitate the creation of dashboards in Tableau.

Ingesting data from multiple platforms into LLMs and rigorously testing the model responses by adjusting parameters such as top_p, top_k, and temperature to ensure optimal performance.

Designing and implementing workflows, including guardrails, to securely process data and prevent exposure of Personally Identifiable Information (PII).

Developing a Slackbot powered by LLMs to provide real-time answers to questions in Slack channels, enhancing support and operational efficiency.

Worked on the existing build and release pipeline of Walmart Mobile Application (iOS/Android).

Converted existing Shell Scripts into Python code to run the Gradle commands during the build process.

Implemented a custom monitoring and diagnostics framework for logging info, warnings, and errors in all existing Python scripts to identify the root cause of build issues.

Designed and developed a FastAPI that takes the PR number as input and determines the performance metrics of the node (M1-NODES, MAC-NODES, OSX, LINUX).

Developed and maintained modular back-end systems using Python and Django, optimizing code for performance, scalability, and security.

Implemented RESTful APIs using Django REST Framework for seamless integration with mobile application release management.

Managed user authentication and authorization workflows using Django's built-in security features and third-party libraries (e.g., OAuth 2, JWT).

Worked with Django ORM for database interactions, optimizing complex queries for performance and reliability.

Automated unit testing and integration testing using PyTest, ensuring code robustness and reliability before release.

Developed a Python/Flask-based REST API with multiple endpoints and exposed it to external customers and later improved the performance from 1 sec to 400 milliseconds.

Implemented authentication and authorization in Flask APIs using libraries like Flask-JWT.

Introduced RabbitMQ in place of threads to improve the overall performance as the number of requests are increasing.

Involved in designing and deploying applications using almost all AWS services (EC2, Route 53, S3, RDS, DynamoDB, SNS, SQS, IAM), focusing on high availability, fault tolerance, and auto-scaling in AWS CloudFormation.

Created Python scripts to totally automate AWS services, including web servers, ELB, CloudFront distribution, database, EC2 and database security groups, S3 bucket, and application configuration.

Added support for AWS S3 and RDS to host static/media files and the database into Amazon Cloud.

Enhanced the existing ETL Python script to a data pipeline using AWS Glue, S3, and Crawlers (Couchbase to Redshift).

Developed a responsive and intuitive claims portal application using JavaScript and React.js, ensuring seamless user interaction and navigation for accessing and managing claims information effectively.

Integrated third-party libraries and APIs into the React.js front end to enhance functionality and enrich user experience, such as integrating data visualization libraries for graphical representation of claims data and integrating authentication libraries for secure user access.

Utilized dependency injection for bootstrapping the web API.

Developed Python scripts that extract data from Couchbase and dump it into AWS Redshift.

Created a Docker file for CI/CD of the containers using Git, Circle CI, Kubernetes, and Rancher.

Automated the continuous integration and deployments using Jenkins, Docker, Ansible, and AWS Cloud Templates.

Used JSON logger and integrated Datadog agent in the application to create dashboards and alerts.

Developed and enhanced an ETL framework that checks DQMs on different databases and gets the counts, validating data between multiple environments (clusters).

Designed and developed an alerting system to framework users whenever the DQM runs, the email alert contains DQM details, and if it fails, an incident is raised and ticket is created for the application teams.

Worked on the framework with multiple modules like Load/Edit, DQM Executer, and Export/Import data from Oracle/Hive/Teradata/Vertica/Druid.

Wrote custom Python scripts for migrating data from Hive to Oracle and vice versa, invoked through a Shell Script using an Autosys job scheduler and scheduled to run every day.

Wrote Python scripts that periodically ingest data into PostgreSQL and serve as the back end to a web server.

Created and executed jobs in different environments, created triggers, and configured jobs using Jenkins.

Loaded and transformed large datasets of structured, semi-structured, and unstructured data using Hadoop/Big Data concepts.

Developed Spark jobs using PySpark in a test environment for faster data processing.

Worked on a Swagger-enabled REST API to serve as an entry point for web UI and integrate with other applications.

Worked on a Node.js Protopath parser project to come up with all possible combinations of Protopath by analyzing the input to predict the combination of incorrect inputs.

Designed and implemented a web application using Python/Django for displaying Maps data for every release and to provide a scope for generating a diff between the data for every release.

Worked on Gradle utility to automate the build and deployment process.

Developed and supported Taxonomy API (REST API) using Python, Flask, Cerberus, and MongoDB.

Wrote Python wrapper for Flask and Eve framework for generating desired results of Taxonomy API.

Created client and server actions and added permissions for admins and non-admin users by restricting individuals for a particular dataset using Flask principal permissions and needs.

Developed an API that asynchronously distributes tasks using RabbitMQ and Celery.

Created a MapReduce job using Python for creating a sync between PTC configs and PTCs to remove unwanted attributes for products in .com.

Developed Spark code using Python for faster data processing and wrote Python normalizations scripts to find duplicate data in different environments.

Wrote scripts to integrate APIs with third-party applications and to import/export data to CSV/Excel formats from different environments using Python and made a Celery action using REST API call.

Conducted data analysis, data validation, data cleaning, and data manipulation with Pandas and NumPy for data visualization.

Developed new and enhanced search features such as Synonym, Canonical, and Abbreviation for optimizing search results and relevancy using JSON, Elasticsearch, and Kibana.

Used Git and Jenkins for continuous integration and deployment.

Extensively used XLSX reader and writer modules to read, write, and analyze data and project the results as per client request.

Worked on the development and maintenance of a content review tool using Python and Django.

Involved in developing back-end operations using Python and SQL by implementing CRUD operations on a user-defined class.

Used Python OOD code for manufacturing quality, monitoring, logging, and debugging code optimization.

Wrote Python scripts to parse XML documents and load data in databases.

Re-engineered various modules for implementing changes and creating an efficient system.

Developed dynamic web pages using Python/Django.

Used Python and Django for XML processing, data exchange, and business logic.