Stock market analytics pipeline with medallion architecture on Databricks
-
Updated
Jan 2, 2026 - Python
#
cloud-data-engineering
Here are 5 public repositories matching this topic...
End-to-end Metadata-Driven Data Engineering framework built on Azure. Features dynamic SQL/REST API ingestion with range pagination, automated schema mapping, and event-driven orchestration. Implements robust CI/CD via GitHub Actions/YAML and automated failure alerting with Logic Apps. Optimized for scalability and DE best practices.
rest-api data-engineering cicd azure-sql-database azure-data-factory etl-pipeline data-engineering-pipeline azure-logic-apps data-orchestration yaml-templating data-lifecycle-management etl-developer metadata-driven-pipelines cloud-data-engineering adls-gen2 azure-data-engineer incremental-load
-
Updated
Jan 16, 2026
End-to-end data engineering pipeline using Azure Blob, Data Factory, dbt, Snowflake, and Streamlit for interactive business analytics. (WIP)
-
Updated
May 9, 2025 - Python
Start Learning From Saylani Institute
-
Updated
Jun 15, 2025 - Jupyter Notebook
Production-style Slowly Changing Dimension (SCD Type 2) pipeline built with Snowflake, dbt, and AWS S3. Demonstrates secure S3 ingestion, layered bronze/silver/gold modeling, dbt snapshots for historical tracking, and analytics-ready views identifying active vs historical records.
python aws sql etl snowflake data-warehouse data-engineering dbt elt data-modeling slowly-changing-dimensions amazon-s3 scd-type-2 analytics-engineering dimensional-modeling modern-data-stack cloud-data-engineering bronze-silver-gold dbt-snapshots
-
Updated
Jan 10, 2026 - Python
Improve this page
Add a description, image, and links to the cloud-data-engineering topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the cloud-data-engineering topic, visit your repo's landing page and select "manage topics."