🚀 Expanding the Stack​

This platform is constantly evolving.

While the core tutorials currently focus on PySpark, Databricks, and Delta Lake, we’re actively expanding into more tools, technologies, and patterns that today’s data engineers and architects rely on daily.

🔧 Upcoming Topics & Tools​

Snowflake Cloud-native data warehousing designed for performance, scale, and simplicity.

Apache Airflow Powerful workflow orchestration — enabling complex, reliable, and scheduled pipelines.

Scala Advanced data processing and functional programming with Spark — for performance-critical jobs.

dbt (Data Build Tool) Modular and testable SQL transformations for modern analytics workflows.

Cloud Platforms: AWS, GCP, Azure End-to-end real-world examples for data engineering on cloud-native infrastructure.

Observability & Data Governance Best practices in monitoring, logging, data lineage, and compliance — critical for production-grade systems.

🧭 What You Can Expect​

• Real-world use cases
• Hands-on tutorials
• Architecture walkthroughs
• Cost and performance tips
• Integration patterns
• Design trade-offs and lessons from the field

We believe great data platforms aren’t just about tools — they’re about clarity, strategy, and maintainability.