Aug 2024 – Dec 2024 · 4 mos · Bengaluru, Karnataka, India · Hybrid

• Scaling job scheduling to execute thousands in parallel
• Transforming data scraping into structured Excel report
• Enabling users to control their privacy with ease.

Jul 2023 – Aug 2024 · 1 yr 1 mo

• > Setup pipelines for CDC to keep multiple databases in sync
• > Leveraged Elasticsearch to build an in-house search engine for multiple products, and fetch nearby localities including tokenization and preprocessing of queries
• > Engineered multiple dashboards to power the operations team to drive sales
• > Involved in the development of multiple products for WaaS from the ground up
• > Gained experience in the implementation of low-level design techniques for multiple functionalities
• > Collaborated with seniors and tech leads to engineer a highly available, mission-critical, data ingestion pipeline for analytical purpose

Jan 2023 – Jun 2023 · 5 mos

• > Developed multiple scripts to scrape data from around 500 web pages
• > Involved in the initial development of one of the products for vendor discovery leveraging Django, MongoDB, ElasticSearch, and PostgreSQL
• > Engineered jobs to maintain data consistency with a few TPA for a few features

Apr 2022 – Dec 2022 · 8 mos

• > Developed search features using ElasticSearch that works in synchronization with PostgreSQL to enable the search functionality.
• > Implemented caching using Redis to offload the read load of aggregates that reduced the API response time from around 250ms to 50ms.
• > Implemented one-time payment services using stripe to maintain the payment history of users in the PostgreSQL tables
• > Inmplemented in-app notification by setting up a pipeling that would trigger multiple jobs like sending FCM Notifications and storing notification data into Redis for future usage
• > Engineered webhooks using Stripe SDK and serverless functions on AWS Lambda to ensure the safe and secure authorization of payments made by the user for the content purchased on the app, in case of any mishap or downtime of the EC2 server.
• > Enabled the master-slave architecture on the database to offload the read-loads onto the slave node and write loads on the master node, where asynchronous replication happens b/w the 2 nodes to maintain data consistency.
• > Implemented an ElasticCache cluster inside the VPC same as with the EC2 to cut off the connection with the internet for security and latency purposes and also to implement caching using Redis and taking regular snapshots of the node to enable fault-tolerance in case of cache invalidation or data lost due to EC2 ram usage spike.
• > Enabled auto-scaling to comply with the incoming load on the servers to maintain 99.99% uptime by scaling up in case of increased API calls and vice-versa based on the parameters of CPU usage using AWS Auto Scaling Group.

Nov 2021 – Mar 2022 · 4 mos

• > Created multiple endpoints using Express.js and MongoDB to onboard users and enable them to match their profiles with the recruiters
• > Developed modules through which users can track their learning progress of the courses listed on the website
• > Added a search and filter option on jobs to ease the job-search process for candidates
• > Deployed the whole backend and frontend on the EC2 server and implemented reverse proxy using Nginx
• > Created separate environment for testing and production purposes both on the frontend as well as the backend
• > Added on-the-fly serverless image resizer/editor to use the same images stored on S3 for different locations on the website but with different resolutions and served them via CloudFront for faster delivery and an added advantage of images being cached.
• > Developed a service to use S3 and Cloudfront as the sole technologies to deliver videos as part of their educational service.

Apr 2021 – Jul 2021 · 3 mos

• Worked on developing APIs using technologies like GraphQL, Nodejs, and MySQL to design and deploy APIs on a dedicated EC2 server along with payments service integration using Razorpay