REST application using serverless mechanisms, AWS API Gateway, AWS Lambda, SAM Created CI/CD in AWS CodePipeline Working on managing Big Data and Geographic objects using Postgres and Postgis.

Reference to Mesh, working for Mesh throught Thirstysprout

Create an architecture for live crawling of multiple websites, which is scalable architecture and it is easy to add new spiders Created custom async spiders using asyncio and aiohttp library Wrote spiders for 50 states, more than 80 websites Created REST app in Flask for calling crawlers directly on demand collecting info Created deployment systems to make flask application scalable and robust using AWS Elastic Beanstalk Using AWS services like Lambda, DynamoDB, SQL to create a scalable serverless crawling system. Created User Management service Created Auth services using AWS Cognito Created Email Notifications service Documented software development methodologies in technical manuals to be used by IT personnel in future projects. Coordinated deployments of new software, feature updates and fixes.

US statutes & laws scraper | Scrapy Scraping and parsing system for United States 50 states laws using Python Scrapy Transforming all data into structured XML • Automatize scraping process using cron jobs Storing data in NoSQL db systems Implementing Flask API endpoints for manually calling scrapers and collect info Simple CRUD project for oil company | Web2Py MVC project created in Web2Py Managing both FE and BE tasks and in support for later bug fixes Event scraping | Scrapy Created system for scraping new and popular events from various different websites. Eventbrite, Ticketmaster and etc. Automatize scraping process using cron jobs Send generated data to client through JSON output Microservices project for fintech startup | Flask Plan and implement microservice architecture for fintech startups Construct various microservices such as One Time Password, User registration and Authentication and etc. Dockerize microservices and deploy on AWS instances using cloudformation and docker compose. Amazon products allergen checking | Flask Created rest endpoints for calling machine learning models on live data Create Machine Learning pipeline system for food label validation and compliance.System used several Neural Network models to receive images of food labels and extract required information such as nutrition facts, allergens, ingredients, weight Create a pipeline accuracy evaluation system to measure end-to-end accuracy as well as accuracy for each individual step Implement unit tests and test-driven development Influencers database | Scrapy & Flask Created scalable scraping system for social media crawling Scraped more than 50 millions of users data from Instagram, FB, Youtube, Twitch Created algorithm which was identifying same users throughout different social media platform Created algorithm for detecting bots Stored all data into Elastic Search for fast searching. Created REST app in Flask to support showing this data