Hello, my name is Darwin Ramesh and I am an aspiring Data Engineer. I am open to internships, on-site in Malaysia or remote.
I am a first year student pursuing a bachelor's degree in Computer Science at Taylor's University. I have an interest in pursuing a future career in Data Engineering/ETL Engineering. I enjoy designing system schemas, understanding how data interfaces with software to create business insights. Within my profile, I have a few public projects to look through where I've used industry standard tools to create scalable and functional ETL pipelines ready for analytical and business insights.
| Project | Tools | Description | Genre |
|---|---|---|---|
| Data-Warehouse | Python, Postgres | A more scalable but still simple medallion architecture ETL pipeline done with postgreSQL and psycopg3 | Data Engineering |
| Databricks_dbt_project | Python, Postgres, dbt, Databricks | A scalable medallion architecture ETL pipeline done in Databricks with dbt | Data Engineering |
| Kafka AWS Streaming pipeline | Python, AWS, Kafka, Docker, SQL | A structured streaming pipeline using Finnhub's api and AWS to host a datalakehouse. No database used, only parquet, glue and athena for compressed and efficient data storage and queribility. | Data Engineering |
| csv-cleaner | Go | A simple and performant CSV cleaner written in Go | Data Processing |
To build working, automated pipelines that are scalable, secure and ready for use. I start with minimal tooling and abstractions used and scaled my projects as I went along in order to understand how pipelines and orchestration happens on a lower-level. As a result, I have a good understanding on why any said tool in my system is used, what they solve and when must they be implemented.
