Snowflake - Datawarehouse and Datalake solutions using AWS

Snowflake - Datawarehouse and Datalake solutions using AWS

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Data engineering and architecting pipelines using snowflake & AWS cloud

Updated on Sep, 2026

Programming, Data Science, Big Data

Duration - 8.5 hours

Training 5 or more people ?

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Snowflake is the next big thing and it is becoming a full-blown data eco-system. With the level of scalability & efficiency in handling massive volumes of data and also with several new concepts in it, this is the right time to wrap your head around Snowflake and have it in your toolkit. This course not only covers the core features of Snowflake but also teaches you how to deploy python/pyspark jobs in AWS Glue and Airflow that communicate with Snowflake, which is one of the most important aspects of building pipelines.

Anyone who has a basic understanding of the cloud and belongs to one of the below backgrounds can benefit from this course :

This course covers :

Most Crucial Aspects of Snowflake in a very practical manner

Writing Python/Spark Jobs in AWS Glue Jobs for data transformation

Real-Time Streaming using Kafka and Snowflake

Interacting with External Functions & use cases

Security Features in Snowflake

Important Note - You need to have an active AWS Account to perform tasks in sections related to Python and PySpark. This course will help you with Snowpro certifications as well

Knowing SQL or at least some prior knowledge in writing queries

Scripting in Python (or any language )

Willingness to explore, learn and put in the extra effort to succeed

An active AWS Account & know-how of basic cloud fundamentals

Prior programming experience in SQL and Python is a must.

Prior basic experience or understanding of cloud services like AWS is important

Check out the detailed breakdown of what’s inside the course

I am a Business oriented Data Architect with a vast experience in the field of Software Development,Distributed processing and data engineering on cloud . I have worked on different cloud platforms such as AWS & GCP and also with on-prem hadoop clusters. I also give seminars on Distributed processing using Spark , real time streaming and analytics and best practices for ETL and data governance.I am also a passionate coder ,love writing and building optimal data pipelines for robust data processing and streaming solutions .

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