Hello. I completed my undergraduate and master's degrees in the United States, majoring in Computer Science and Data Science, respectively. Currently, I am working as a data engineer at a healthcare company. To briefly describe my daily responsibilities: I use AWS and Airflow to ingest data daily and perform ETL processes. I also monitor the data flow and implement programs whenever issues arise or there is room for improvement. For data monitoring, I primarily use AWS CloudWatch and a program called Splunk. The technologies I currently use at work include Python, AWS, SQL, and more. Recently, we have been migrating to GCP, so I am gaining experience with both AWS and GCP simultaneously.
In 2022, nearly 80% of the company's data and pipelines completed migration to GCP, and I am now working extensively with BigQuery, GCS, and GKE. I am also handling overall IaC tasks using Docker containers and Terraform.
The biggest thing I've realized while working as a data engineer is this: with new technologies emerging every day, will the tools I'm using now become obsolete? If so, why? Can that new technology really replace this one? Are there no downsides? Indeed, finding answers to all these questions seems very difficult. However, through that process, I noticed one commonality. When you dive deep, they are mostly similar. In other words, if you dig into one thing properly, learning other technologies becomes much easier. I want to frequently mention this mechanism in my lectures. I want to share all the knowledge I currently have with you. I will do my best to be your guide.
I, Simon Kim, will present fun and easy-to-understand lectures for you. I promise to become a better person by constantly communicating with all of you. It is my great happiness to watch your skills improve.
I promise to become a better person. Watching your skills improve is a great source of happiness for me. Authored Book: Introduction to AWS for Immediate Practical Use