My work is primarily focused on the product-platform backend APIs and the customer-data ingestion pipelines.Tech stack: SQL, Python, Fast API, AWS-S3, API Gateway, Lambda, EC2, Snowflake DB, MySQL DB, Airflow.

Data:*[Univision's PrendeTV] : Built ETL Pipelines to pre-process raw streaming data (hourly) and daily video catalogs so that it remains available and usable for future analytics. Implemented parallel concurrent threads as a feasible architecture on Google Cloud Run to reduce the cost and time to run these pipelines.Made tools and utilities for performing data loading and ingestion, evaluating the technical trade-offs of every decision and optimizing… Show more Data:*[Univision's PrendeTV] : Built ETL Pipelines to pre-process raw streaming data (hourly) and daily video catalogs so that it remains available and usable for future analytics. Implemented parallel concurrent threads as a feasible architecture on Google Cloud Run to reduce the cost and time to run these pipelines.Made tools and utilities for performing data loading and ingestion, evaluating the technical trade-offs of every decision and optimizing it.SDE:*[Machine Learning Experimentation Studio] : An entire webapp built for the purpose of explaining a ML dataset problem. It helps you find the best model(s) along with explanations for each model. I picked up up a few data-science skills while working on the backend and it also sharpened my skills in serverless computing services.*[Data Exploration Studio] : Built up the entire studio from scratch leveraging Vue.js, D3.js on the client side, and Python/AWS Lambda, S3, DynamoDB and API Gateway on the server side. The project focuses on exploring and visualizing a dataset, getting its important summary details, diving deep into the data Show less