Best Data Engineering Tools in the AI Era: Databricks, Snowflake, dbt, Airflow & More

Data Engineering is changing fast. In the AI era, Data Engineers are no longer just building traditional ETL pipelines. They are designing trusted, governed, real-time, AI-ready data ecosystems.

In this video, we explain the most important modern Data Engineering tools and how they fit together: Databricks, Snowflake, BigQuery, Redshift, Microsoft Fabric, dbt, Airflow, Azure Data Factory, Trino, Kafka, Spark, PySpark, and Delta Lake.

You will learn why tool categories matter, when Databricks is a strong option, how Snowflake and cloud warehouses fit into modern analytics, and why governance, data quality, metadata, lineage, orchestration, and streaming are now critical for AI-ready platforms.

The goal is no longer just to move data. The goal is to create reliable data products that can support analytics, machine learning, AI agents, and intelligent applications.

In the AI era, the best Data Engineers will not only move data. They will build the trusted foundation behind intelligent systems.

Видео Best Data Engineering Tools in the AI Era: Databricks, Snowflake, dbt, Airflow & More канала Alberto Gaytan