LUCKY MASRAM

Had a detailed discussion with the client to understand the project requirements and objectives. Designed system and procedures according to the needs of the client and developed a timeline to effciently achieve project objectives. Developed, tested, debugged, and documented 4+ software applications. Used established coding standards and methodologies and coached 2 junior engineers on best practices. Worked within an agile team, contributing to 100% continuous improvement and deployment (CICD).

Designed and developed REST API to insert and update data using AWS API Gateway, Cognito for user authorization and Lambda for processing of data. Implemented CI/CD for all the resources and pipeline. Continuously monitored the performance of the project and debugged and resolved any error that occurred within a short period. Made sure that the client does not face any signifcant disruptions. Drafted API Documentation using Postman.

Used Python for developing scrapping functions to extract images and transaction details. Used Selenium tool to check all test cases and ensure that production code runs smoothly. Developed an automation mechanism to clean and process incoming data and store it systematically in Google Sheets to facilitate fast retrieval and processing for the client. Use of logical recursion eliminated the need to manually process the incoming data and ensured that the process would run continuously without the need for continuous monitoring. This led to signifcant savings in terms of monitoring and manual triggering of the script for the client. Use of an automation mechanism eliminated the need to manually process the incoming data and ensured that the process would run continuously without the need for continuous monitoring. This led to signifcant savings in terms of man-hours for the development team as well as for the client. At present the system is running seamlessly as per the requirements of the client having a success ratio of 98.99% with minimum disruptions.

Automated the ETL Pipeline, which was triggered every 2 hours to the need of requirement. Further optimized the ETL pipeline and reduced the time execution by 15%.

Designed multiple ETL pipelines to cater to multiple users ensuring incoming data is appropriately transformed and processed and loaded into the data warehouse for the use of the client. Ensured the client has multiple channels (email, FTP, and Amazon S3) for sending unprocessed data to the pipeline. This provided flexibility to the client and ensured the continuous feeding of data to ETL pipelines. Used AWS services including Glue, EC2, Lambda, and S3. Used a variety of AWS services including Glue, EC2, Lambda, and S3. Terraform, SQS, etc, for functions such as messaging, data storage, data processing, etc. Providing users a smooth and hassle-free experience while working with ETL pipelines. Transferred the processed data to the forecasting team for developing forecasting models and made a backup of the processed data on AWS S3. Received the forecast results from the forecasting team and processed them using the developed ETL pipelines as per the acquirement of the client. Backed up the forecast results and the processed data in AWS S3.