Pragya is a Python Developer with 4. 5 years of experience in full-stack development, specializing in AWS, Django, and React.
Proven ability to deploy AWS services using Infrastructure as Code.
Successfully migrated complex systems to modern architectures.
Designed and developed robust validation frameworks for data integrity.
Implemented CI/CD frameworks leading to efficient deployment cycles.
Reduced processing time from 1 day to 5-6 hours for 15 million records.
Migrated a complex system to AWS services, enhancing performance and reliability.
Developed end-to-end systems for real-time data analytics on AWS.
Overview: Content Elbert N23 is a web-based application designed to automate manual work processes using machine learning models. Responsibilities: Deployed AWS services using CloudFormation for infrastructure as code. Migrated the system to Python, RDS PostgreSQL, AWS Redshift, AWS Lambda, Glue, and implemented job scheduling on Redis and Step Functions. Designed and developed a validation framework using Django, React, Python, Lambda, ECS, and ECR to annotate predicted labels. Developed a UI framework with React to display extracted JSON data and implemented parallel file processing. Implemented feature-based user roles and responsibility using React and Django. Utilized asynchronous Lambda invoke via Django to process annotated data for reprocessing. Established CI/CD pipelines using Jenkins and IaC with Terraform for continuous integration and deployment. Enhanced user authentication by adapting the application to OKTA user groups. Significantly improved file processing performance, reducing processing time from 1 day to 5-6 hours for 15 million records. Developed Python scripts to extract data from `gz` format files, convert to CSV or JSON, and load the data into Redshift. Designed and implemented ETL scripts for regular ETL jobs using AWS Lambda, Glue, and crawler to process millions of unstructured social media records. Developed a framework for cleaning source data using Python, SQL, Glue, and crawler.
Key outcomes:
Successfully migrated the system to Python, RDS PostgreSQL, AWS Redshift, AWS Lambda, Glue, and implemented job scheduling on Redis and Step Functions.
Significantly improved file processing performance, reducing processing time from 1 day to 5-6 hours for 15 million records.
Designed and developed a robust validation framework using Django, React, Python, Lambda, ECS, and ECR for annotating predicted labels.
Overview: Developed a sophisticated data product, 'Future Enterprise,' designed to empower organizational leaders with actionable insights for strategic decision-making and sustainable growth. Responsibilities: Contributed to the development of enterprise data products, enabling organizations to make informed decisions crucial for future growth. Developed a UI framework using React to display extracted JSON data. Assisted with the development of products based on data insights, ensuring accurate and actionable data. Executed tasks related to data cleaning and preparation, enhancing data quality and reliability. Designed and developed modular and reusable React components to create a sophisticated user interface. Collaborated with cross-functional teams to achieve project milestones and ensure successful project delivery. Executed comprehensive unit and end-to-end testing for React components, ensuring their reliability and robustness. Developed and maintained data pipelines for efficient data flow and processing. Implemented best practices for data security and privacy, ensuring compliance with relevant regulations. Conducted data analysis and visualization to provide insights and support decision-making processes.
Key outcomes:
Designed and developed modular and reusable React components, contributing to a scalable and maintainable front-end architecture.
Implemented best practices for data security and privacy, ensuring compliance with relevant regulations.
Developed and maintained data pipelines for efficient data flow and processing.
Pragya
Python Full Stack