- MIS master's graduate with several years of experience in full stack development in an Agile environment.
- Experienced in analyzing, designing, developing, testing, and debugging software solutions using principles of responsive web design.
Contributed to the development of the automation tool using React, focusing on the functionalities of workflows and JSTs(JSON Schema Transformations) that are key parts of the tool and adapters that connect to several external systems seamlessly.
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Collaborated with a cross-functional team to deliver high-quality code on schedule.
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Participated in regular code reviews assigned as JIRA tickets, providing constructive feedback that enhanced code quality
and team collaboration.
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Implemented automated testing procedures in Git pipeline using internal Cypress testing library, reducing manual testing
efforts of the prebuilt automations that customers leverage to rapidly adopt network automation for specific use cases.
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Led a team of 2 support engineers in delivering post-implementation technical assistance to customers.
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Assisted in the planning and implementation of a high availability architecture and load balancing for the automation tool in production environments of customers to achieve minimal downtime.
Built and migrated web applications from PHP/SQL stack to Node.js, React/Next, PostgreSQL stack, integrated with Salesforce CRM and deployed with Heroku.
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Built, managed and deployed a stack of microsites with AWS Serverless components - Lambda, DynamoDB, S3, SQS.
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Developed web projects and fixed bugs on the legacy web application built using PHP.
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Designed and built frontend of lightning web components on Salesforce.
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Developed google analytics dashboards to visualize data from the web application.
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Performed sentiment analysis on official twitter handles to get public insights.
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Created proof of concepts with latest technologies for implementation into the web application.
(Tech Stack: Python ML libraries, Azure analytics, Power-BI, Gephi)
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Delivered lectures to master’s students on social media analytics, Twitter’s streaming data, Azure stream analytics, Power- BI and Gephi., data cleaning, topic modelling (analyzing and classifying large volumes of text data) and sentiment analysis (emotion AI for text analysis and language processing) using Python’s libraries like pandas, nltk, tweepy, matplotlib etc.,
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Evaluated students’ exams and helped them debug and fix problems in their academic projects.