In my current role, I have focused on understanding and optimizing the existing architecture built on Dagster. As data volumes and the number of clients continue to grow, I have been working on improving the data pipeline to ensure scalability and performance. I am also leading the adoption and integration of DBT for transformation workflows. Additionally, I am involved in transitioning to Apache Iceberg tables on AWS Athena, aimed at enhancing processing speed and cost efficiency.

With extensive experience in building and optimizing end-to-end data pipelines, I've consistently harnessed the power of technology to extract, transform, and load data seamlessly. My expertise lies at the intersection of cutting-edge technologies and practical application, enabling me to drive real-time analytics, text analysis, and predictive modeling. My toolset includes Python, SQL, S3, RDS, AWS Lambdas, and SAM

As one of the first engineers to join the company, I have worked and built many projects from scratch. Tech Stack : Python, SQL, S3, RDS, AWS Lambdas and SAM- Built scalable and resilient data pipelines to extract information from our customer, transform the data supporting our schema and load in our system.- Built data pipelines with complete ETL flow for real time streaming and real time analytics.- Implemented fuzzy logic and elastic search for a text match engine that… Show more As one of the first engineers to join the company, I have worked and built many projects from scratch. Tech Stack : Python, SQL, S3, RDS, AWS Lambdas and SAM- Built scalable and resilient data pipelines to extract information from our customer, transform the data supporting our schema and load in our system.- Built data pipelines with complete ETL flow for real time streaming and real time analytics.- Implemented fuzzy logic and elastic search for a text match engine that searches our master database and returns the most closely matched string.- Build financial models along with the underwriting team that computes companies metrics.- Implemented a time-series forecasting model to predict what the next month revenue would be for our customer. Show less

Tech Stack : Python, AWS Redshift, POSTGRESQL, MYSQL, MONGO, AWS Kinesis- Built new data pipelines from scratch to transfer data from data-lake to data-warehouse.- Built data pipelines with complete ETL flow for real time streaming and real time analytics.- Built data pipeline to transfer data from databases such as mongo, postgres to data-lake (aws redshift)

Tech Stack: Node.Js, Python, AWS (Athena, S3, SQS, SES, API Gateway), Dynamo DB & Tableau.- Developed the whole system (DB Schema, Modules, API Url).- Designed features from scratch such as Achievements Badges, Channels forCommunication, Leaderboards & automated testing scripts.- Used Tableau for data visualization & MS-Excel for data interpretations to analyze thepatterns.- Acted as a Tech Lead & mentor a team of 4 developers.

Online Mocks is a non-profit company that lets students take a simulated examination for CAT & other competitive tests.Tech Stack: MeteorJS, BlazeJS, NodeJS, Javascript, HTML5, CSS3, MongoDB, Azure, Nginx.- Designed, owned, and maintained as a sole developer of the product.- Used MeteorJS & designed a Hybrid mobile app (Know Doubt) by developing databaseschema, streamlined & optimised new features, and released on app store in just 4 months.

- Gave introduction of DSA topics to MTech fresher students and helped them revise. - Managed lab sessions and made test-cases using python.