Snowflake provides a cost-efficient cloud data warehouse. It is capable of virtually unlimited storage and compute through the use of MPP clusters.

I have worked with snowflake to create highly performant pipelines. I have worked with snowflake tasks and streams to build pipelines for batch data and snowpipes for the creation of streaming pipelines.

Airflow is a simple to use and lightweight orchestrator based on cron expressions.

I have used Airflow both as an open-source service and as a hosted service on AWS. During my use of the tool, I have worked with various operators like python, sql, bash, ecsoperator etc

Data Build Tool enables the developers to efficiently transform the data. I have used DBT a couple of times in my data pipelines to ensure that my transformations are easily implemented and the plus point is that the DBT models are properly versioned.

Git is an industry standard when it comes to code versioning. I have worked with Git extensively during my past projects. As a version control system, it serves the dual purpose of creating a tracker for your work as well as a choice which promotes team collaboration.

Django is a framework in Python which allows rapid development of web applications. 

I have created several web applications using Django during my initial days of being a tech employee. Most projects deployed on to AWS cloud environments.

I have used Google's Gemini engine to create several conversational and domain knowledge based AI systems.

I have integrated them with my web applications to create  a dedicated AI response Bot.