Building scalable search

Working as part of the back-end engineering team in Trial Run(http://www.fractalanalytics.com/trial-run). Trial Run is a 'Test-Measure-Adapt'​ experimentation workbench, provided as a web application. ● Design and develop a REST API for back-end modules, which facilitate clients to design new businessexperiments and later run, analyze them.● Worked on the Spark data aggregation pipeline to process client data as raw files to be used by the back-end API.●Improve backend application runtime by 20 percent by separating out computation intensive KNN calculations into a batch application.● Worked closely with Fortune 500 client to do data quality checks and implement new client specificrequirements in the application.● Set up the complete environment on AWS and internal servers for the application deployment.● Coordinate with client representative team to Implement new data quality checks and client specific requirements in the application.Technology Stack: Python, Django / Django Rest Framework, Pandas (Python data analysis library), Apache Spark (PySpark), PostgreSQL, Jenkins, AWS, RabbitMQ, Celery, SQLAlchemy, REST API.

Worked on RET data visualization and analytical tool.●Wrote complete data parsing pipeline to process raw text and XML files to find relevant information which can be used in dashboard.●Develop web-based dashboard to give developers detail insights using current and historical data to make more informed decisions.Technology Stack: Python Django, Pandas, JavaScript, JQuery

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