Mayurkumar Tank is a highly motivated Python programmer with extensive experience in developing web scraping frameworks and ETL processes. He has demonstrated leadership by managing a team of 14 developers and has a strong capability in cloud deployments and serverless architectures. His technical expertise includes proficiency in Python, PostgreSQL, Docker, and Kubernetes, making him well-equipped to handle complex data-driven projects.
Led a team of 14 developers for robust ETL workflow implementation.
Implemented diverse data extraction modules from websites and PDF documents.
Developed end-to-end automation scripts for data integration with Zoho and Jira.
Managed container deployments with Docker and Kubernetes for data extraction and processing.
Applied various machine learning algorithms for accurate price prediction.
Engineered scalable ETL pipelines leveraging Google Cloud Pub/Sub and Big Query for efficient data processing.
Overview: This project focused on implementing a robust ETL workflow for diamond and live data. Responsibilities: Led a 14-developer team to implement ETL for diamond and live data using Informatica and Python. Utilized SQL and data warehousing programs for data analysis and employed dashboard visualization tools.
Key outcomes:
Implemented a robust workflow using Directed Acyclic Graphs (DAGs) for efficient data orchestration.
Leveraged RESTful APIs to access data from various suppliers.
Overview: This personal project involved scraping bestseller products and various other products from e-commerce sites, including solving captchas. Responsibilities: Scraped bestsellers and diverse products, solved captchas, and extracted data using BeautifulSoup4, JSON, requests, and Selenium.
Key outcomes:
Developed a function to solve captchas during web scraping.
Successfully scraped diverse e-commerce products.
Key outcomes:
Developed web scraper modules to retrieve, clean, and store data efficiently.
Implemented machine learning algorithms (Linear Regression, Random Forest, Gradient Boosting) to predict prices accurately.
Leveraged Google Cloud Pub/Sub for scalable and automated data ingestion.
Key outcomes:
Developed a function to solve captchas during web scraping.
Built a data pipeline to process both batch and streaming data for real-time and periodic analysis.
Successfully scraped diverse e-commerce products and social media engagement metrics.
Mayurkumar Tank
Full Stack Developer