I built a Netflix data pipeline that stages raw content data in Amazon S3 and loads it into Snowflake. With dbt, I transformed the data through raw, staging, and serving layers, added tests, and documented model lineage.
For an e-commerce sales pipeline, I used Databricks to clean incoming data and model it into fact and dimension tables in PostgreSQL. I orchestrated recurring jobs with Apache Airflow and validated outputs with SQL.
At Arlig Technologies, I optimized SQL queries and MySQL indexing for a production application, reducing data retrieval latency by 30%. I also deployed containerized services to AWS EC2 and S3.
I’m a Computer Science undergraduate at BMS Institute of Technology & Management, focused on data engineering. My projects and experience use Python, SQL, dbt, Snowflake, and Apache Airflow to prepare and validate data for analytics.
