Oct 2022 – Jul 2024 · 1 yr 9 mos

• Working with 𝐂𝐥𝐨𝐮𝐝 𝐌𝐢𝐠𝐫𝐚𝐭𝐢𝐨𝐧𝐬 𝐓𝐞𝐚𝐦 to enable migrations from On Prem to Cloud
• Significantly improved the success rate of cloud migrations(JIRA), a critical revenue driver, as measured by an increase from 87% to a targeted 95%. This was achieved by identifying and resolving issues across multiple migration phases, including export, import, user migration, and attachment failures. Enhanced Atlassian's organizational efficiency by providing reliable and efficient cloud migration solutions, directly impacting the company's revenue stream.
• Optimized the Cloud Migrations team's productivity and efficiency as measured by a 50-hour monthly reduction in manual analysis time. This was achieved by developing an automated system for Plan Success Rate (PSR) analysis, which expedited debugging cycles and improved system reliability. Improved the reliability of cloud migrations, as measured by the stabilization of system reliability, potentially saving 700 developer hours per month.
• Developed a platform Customer Feedback Ecosystem, it crawled different websites and platforms like Twitter, Linkedin, Facebook, Public forums, private forums, news articles, blogs, etc to crawl any and every data related to Atlassian Products. The purpose was to give Business, Product and Sales team a holistic view on how are customer sentiments around various products to drive out the strategies more data driven way
• Utilizing real-time web crawling to gather pertinent data, structuring it through Robotic Process Automation (RPA) and Natural Language Processing (NLP), conducting thematic and sentiment analysis, and providing actionable insights to product teams for informed decision-making..

Sep 2021 – Oct 2022 · 1 yr 1 mo

• Working on 𝗦𝗰𝗵𝗲𝗺𝗮 𝗶𝗻𝘁𝗲𝗿𝗻𝗮𝘁𝗶𝗼𝗻𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻, Re-modelling the entire Architecture of Content Management System in such a way that single Database supports storage of Meta Data related to all assets deprecating Multi-tenant Database architecture and make it available to multiple downstream services.
• Moving from RDBMS to Document DB, using Debezium to implement the CDC pipeline for indexing
• Created a Framework from Scratch to Migrate Data from RDBMS to Document DB, having all possible data modelling relationships ensuring referential integrity

Jul 2021 – Sep 2021 · 2 mos

• Built a Microservice from Scratch to identify precision of Geo-location of User and Restaurant Addresses and using this information to take decisions around ETA Prediction, Delivery charges, number of rider calls allowed, performed complex computations on more than 250 million geo-spatial points on Daily basis , was built in Python, Go
• Built Algorithms for prediction of correct Geo-location( coordinates ) of User and Restaurant Addresses which optimized Delivery time and ETA prediction, saving us around 60 paise/order for orders placed from such addresses

Jan 2019 – Jul 2021 · 2 yrs 6 mos

• Built a Data Pipeline for real time streaming events, processing over 5 billion streaming data points/day. Used Apache Flink Distributed data processing engine. The data pipeline was fully fault-tolerant and data drop rate was reduced to zero, Kafka was used as a distributed messaging system, worked on Java and used Redis as cache, It aggregates all Data points as they stream into our systems and was able to tell the number of Ads delivered in real time and reduced the under-delivery and over-delivery of Ads by 11% and 7%.
• Worked on various Microservices like POI Service, Cell Service, Restaurant Serviceability, Dynamic Delivery Areas, Entities and establishments based Exclusions built over Go, setted up CRON based workers built on Go for increased throughput and reduced memory usage, CPU Utilization
• Created POIs ( Geo-Fences) for regions and Sub-localities having high frequency of orders by creating cluster of spatial co-ordinates using TFIDF model and DBSCAN, for optimizing core services, identifying Exit/Entry points for localities on dynamic windows, used it to reduce Google Places and Geocoding API hits by nearly 53%, used Python, PHP, JavaScript.
• Revamped the Similarity logic for Restaurants recommendations shown on Search Page and Restaurant page of Zomato
• Created Restaurant and User side POIs(Point of Interests) for optimizing core services, identifying Exit/Entry points for localities on dynamic windows, n-order batching, dynamic Address Templates, better location accuracy, improved Dine-out Recommendations

Mar 2019 – Mar 2019 · 0 mo · Bengaluru Area, India

• Developed a feature for Live Class on Unacademy Plus in React JS, a Pen for Canvas with anti-aliasing and whose stroke width changes with the speed and gives a smoother transition and zero sharp edges.

Dec 2018 – Mar 2019 · 3 mos · Bengaluru, Karnataka, India · Remote

• Mentoring computer science students and professionals to get their dream jobs in product companies and startups through career guidance sessions, doubt solving sessions, resume review sessions and mock interviews.

Jun 2018 – Jul 2018 · 1 mo · On-site

Apr 2018 – Jun 2018 · 2 mos

• Developed a Python Script which fetches Tasks from JIRA Dashboard satisfying a JQL Query and then assign those tasks to team members in a pre-defined order following local time and availability constraints , updates the tasks assigned table in Gsheets and sends a personal notification to the member on Slack about task Assigned to him, used Microsoft Bot Framework as a wrapper on slack API for interacting with any channel or users on Slack.
• Wrote and Automated end to end test cases for multiple webpages of app.vwo.com following Page Object Model in Node.js using protractor and Jasmine framework

Jun 2017 – Jul 2017 · 1 mo · Gurgaon, India

• Being an Early intern, it gave me a great handful experiences
• I got to Develop a Visual Basic Application for Deeper Insights on OSI( Open Systems Interconnection) model and Troubleshooting Problems encountered while Working on Transport, Network, Data link or Physical Layer.
• Learnt about Web Services and hosted a Server on RHEL( Red Hat Enterprise Linux) OS by creating a Virtual Machine using VMware.