Viraj Parab

This shopping mall management system is a Node.js- and Android-based system. The data was loaded using CSV files; we designed a Node.js server to extract, transform, and load the data in Elasticsearch. We also used PostgreSQL to read Android data while talking to APIs exposed by Node.js. The code was hosted on AWS EC2 and then moved to ECS and provisioned using a CDK script. We used Jenkins for CI/CD.

I worked as a back-end lead and Elasticsearch expert in the team.

This is an ETL-based project with millions of pieces of data generated after processing input data.

For 2.5 years, I worked as part of a team and was mainly focused on the back end and DevOps. I was also responsible for the release cycle and delivering items to production. The project had an ETL cycle of 4–8 hours as the amount of data was enormous. The front end was connected to a Go-based microservice architecture. The data and time required for ETL were crucial for the clients as they had business hours starting after ETL. I also worked as part of the performance team that oversaw the performance of ETL and the Go microservices.

This Node.js- and React-based app provides a way to store a user's filter for a large data management site.

I largely worked on the back end (Go, Node.js) and DevOps. We used AWS (Fargate clusters, Aurora, and Serverless) for the infrastructure and used AWS CDK for provisioning. I also set up monitoring tools Splunk and Prometheus, and Grafana and created automated CI/CD pipelines using Jenkins.

This web app system helps scientists store large astronomy files with features like linkage and lineage between the files. It also has profile management, integrated files, and an editing tool.

I created the proof of concept as a solo developer and pitched it to the client.

The app enables you to manage your documents easily:
• Scan with a camera or choose photos from Camera Roll. You can scan as many pages as you want.
• Convert your scans into editable text with OCR (optical character recognition) technology.
• Print scanned documents and the text from your clipboard, attachments to emails, documents, and webpages.
• Edit scans perspective and borders, apply filters, adjust contrast, and correct or change the orientation.
• Sign docs right on the screen of your device! Create and save one or more signatures and add to scans whenever you need.
• Highlight the key points of your scans to glean the main idea at a glance.
• Store all your scans in Drive.
• Share scans separately or send a number of files in one PDF file via mail, WhatsApp, or any messenger.
• Upload your scans to Dropbox, Evernote, Google Drive, Box, and more by single tap on the "Copy to" button (make sure the third-party app you are sharing to has been installed on your device).

Accurate scans, simple editing, and sharing: Document Buddy is your indispensable companion for studies, home finances, and business use!

I was a senior back-end engineer for an API transaction company where I designed and built a fraud detection system for card payments. The system utilized a rule-based mechanism to detect fraud in real time, with a detection process completed within milliseconds. I rebuilt the rules and decision-making system to meet our client's needs better. My technical expertise in Go, Node.js, and AWS allowed for the smooth deployment of the system, with databases such as MongoDB and PostgreSQL utilized to store and manage data.

Access Management System was deployed on Amazon EKS, deploying microservices for scalable access control. Leveraging Prometheus and Grafana, the system ensures real-time monitoring. It manages diverse data entities, employing a graph database for intricate user-entity relationships. Robust auditing logs all access activities, while forensic capabilities aid post-incident analysis. The user-friendly interface simplifies access control configuration. Engineered for scalability and compliance, the system meets security standards. Overall, it stands as a benchmark for secure data governance, offering a comprehensive suite for efficient, monitored, and audited access in a dynamic environment.

I created and implemented an automated trading setup using Pine Script on the TradingView platform. I developed and backtested diverse trading algorithms, including SMA, EMA, and RSA, specifically tailored to India's Banking Index Fund. The setup generated trading alerts based on these algorithms, providing valuable insights and facilitating timely buy/sell decisions. Rigorous backtesting over a one-year period ensured the reliability and robustness of the trading strategies. The system's effectiveness was further enhanced through continuous optimization and risk management. This project stands as a testament to successful algorithmic trading in the specific context of the Indian banking sector, providing a valuable tool for informed and data-driven trading decisions.