Snowflake with DBT on AWS for Freshers

This beginner-friendly course introduces freshers to modern data engineering using Snowflake and dbt (data build tool) on AWS. It covers foundational concepts of cloud data warehousing, ELT pipelines, and infrastructure basics. Students will learn to build, transform, and manage data pipelines using Snowflake’s scalable architecture, dbt’s modular transformation framework, and AWS services like S3 and EC2. By the end of the course, learners will be able to create production-grade data workflows and understand end-to-end pipeline orchestration in a cloud environment.

Why Snowflake and DBT Are So Popular:

1. Everyone’s moving to cloud warehouses.

• • Companies are migrating from on-prem (like Oracle, Teradata) to cloud-native platforms like Snowflake, Databricks, BigQuery, Redshift.
  • Snowflake has an edge because it’s easier to manage (no tuning, no sizing complexity).

2. DBT is now the standard for data transformation (T in ELT).

• • DBT allows SQL users (not just engineers) to build, test, and document data pipelines.
  • It’s replacing messy hand-coded transformation scripts.
  • Companies love DBT because it brings software engineering best practices (testing, versioning, CI/CD) into data projects.

3. Companies realize “data quality” is critical.

• • It’s not enough to have data — it must be trusted, tested, and documented.
  • DBT helps formalize all that.