I started my career in Data with an internship at BMC Software Inc where I first got hands-on experience in database systems. I worked on a NLP project to convert natural language statements into database queries - we worked with PostgresSQL and Elastic Search. This gave me foundational experience in database systems and querying.

After completing my bachelors I started working at Publicis Sapient as a Data Engineer - I was responsible for building a data engineering platform from scratch for clients in the retail and advertisement sectors - I built and scaled the platform initially serving a single client and region to 13 clients across 7 regions, processing over 4K reports daily and managing 20TB of data over 1.5 years while reducing cloud costs by 20% and maintaining data quality by automating manual validation processes thereby saving 15 hours of QA time per week.

To further enhance my theoretical knowledge I decided to pursue a masters degree in Computer Engineering at New York University.

At NYU, I got an opportunity to work as a Teaching Assistant with Prof Dan Gode for the course Dealing with Data and Intro to Python. Along with the TA responsibilities I also did adhoc RA work eg. created a python package to fetch and parse US SEC 10K and 10Q filings into structured data frames for further analysis. I also created and launched two websites for courses “Database for Business Analytics” and “Data Visualization” at NYU Stern School of Business starting Summer 24.

I also hold several certifications, including the Associate and Professional Developer Certifications for Apache Spark and the Google Cloud Professional Data Engineer. I’ve also recently completed training in DBT and Databricks, enhancing my ability to work with modern data engineering platforms.