Modern Data Engineering Stack Explained 🤯 | 8 Layers Every Engineer Must Know

Modern data platforms are no longer built with isolated tools. Today’s data engineering systems are powered by connected layers working together — from ingestion and streaming to orchestration, analytics, and governance. In this BazAI breakdown, we explore the 8 core layers of the modern open-source data engineering stack and explain how technologies like Kafka, Spark, Airflow, dbt, Iceberg, Trino, and DataHub fit together into one scalable architecture. This video covers: ✅ Data Ingestion ✅ Real-Time Streaming ✅ Distributed Processing ✅ Workflow Orchestration ✅ Data Transformation ✅ Storage & Lakehouse Formats ✅ Query & Analytics Engines ✅ Data Quality & Governance You’ll learn how modern enterprises build scalable data platforms for analytics, machine learning, AI pipelines, business intelligence, and real-time applications using open-source technologies. Perfect for: Data engineers Cloud engineers AI engineers Backend developers DevOps engineers Data architects Analytics engineers Technologies covered include: Apache Kafka Apache Spark Apache Airflow dbt Core Iceberg Delta Lake DuckDB Trino ClickHouse Flink Ray DataHub OpenMetadata And many more. Subscribe to BazAI for deep engineering breakdowns, AI systems, cloud-native architectures, autonomous agents, and next-generation infrastructure explained simply.