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amee-joshi-data-engineering-portfolio

Provides Azure data engineering patterns with Medallion architecture and ETL/ELT pipelines.

5|1|Updated May 16, 2026
Search Tags:#data engineering#Azure#dimensional modeling#ETL/ELT#data lakehouse#Medallion architecture
One-click install
npx skills add https://github.com/Aradotso/data-skills --skill amee-joshi-data-engineering-portfolio
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: amee-joshi-data-engineering-portfolio
Source: https://github.com/Aradotso/data-skills/tree/main/skills/amee-joshi-data-engineering-portfolio
Command: npx skills add https://github.com/Aradotso/data-skills --skill amee-joshi-data-engineering-portfolio

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires azure, databricks, sqlserver, powerbi, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill unit offers reference examples and patterns for building end-to-end data engineering solutions with Azure services, demonstrating scalable data platforms that leverage Medallion architecture and cloud-native technologies.

Core Features & Use Cases

  • Azure Data Engineering Patterns: Implements various Azure data engineering patterns, including Medallion architecture, for scalable data platforms.
  • Medallion Architecture: Demonstrates the Bronze-Silver-Gold architecture for data pipelines and analytics-ready datasets.
  • Data Lakehouse: Implements data lakehouse patterns with Delta Lake for efficient data management and analytics.
  • Dimensional Modeling: Provides dimensional modeling examples using SQL Server for data warehousing.
  • ETL/ELT Pipeline Design: Offers ETL/ELT pipeline design patterns with incremental loading for efficient data processing.
  • BI Reporting: Includes examples of Power BI reporting solutions for data visualization.
  • Use Case: This skill is ideal for data engineers and architects looking to implement robust and scalable data platforms with Azure and Databricks.

Quick Start

To view the Azure Databricks Retail Lakehouse project, visit the repository 'azure-databricks-end-to-end-retail-lakehouse'.

Frequently Asked Questions about amee-joshi-data-engineering-portfolio

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build ETL pipelines using Azure Databricks and Medallion architecture?▼

Implement dimensional modeling in SQL Server for data warehousing by designing star schemas and applying ETL/ELT pipeline patterns with incremental loading to populate analytics-ready datasets efficiently. This Skill provides reference examples for structuring these models.

What is the best way to implement a data lakehouse with Delta Lake on Azure?▼

Power BI connects to Azure data lakehouse architectures by consuming analytics-ready Gold layer datasets built through ETL/ELT pipelines. This Skill includes examples of Power BI reporting solutions for visualizing data processed via Medallion architecture.

How do I implement dimensional modeling in SQL Server for data warehousing?▼

Implement dimensional modeling in SQL Server for data warehousing by designing star schemas and applying ETL/ELT pipeline patterns with incremental loading to populate analytics-ready datasets efficiently. This Skill provides reference examples for structuring these models.

Does Power BI work with Azure data lakehouse architectures?▼

Power BI connects to Azure data lakehouse architectures by consuming analytics-ready Gold layer datasets built through ETL/ELT pipelines. This Skill includes examples of Power BI reporting solutions for visualizing data processed via Medallion architecture.

Do I need Azure and Databricks to use Medallion architecture patterns?▼

Azure and Databricks are required dependencies to implement the scalable cloud-native data platforms and Medallion architecture patterns demonstrated in this Skill, ensuring proper data lakehouse management and ETL/ELT pipeline execution.

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