Welcome to my Data Engineering & Analytics portfolio.
This repository is a curated collection of real-world, end-to-end data projects demonstrating my ability to work across the entire data lifecycle — from raw data ingestion and scalable data pipelines to analytics and business reporting.
I am a Data Engineer & Data Analyst with 8+ years of professional experience as an Android Developer, where I worked extensively on the full application lifecycle — requirement gathering, system design, development, testing, deployment, and production support via the Google Play Store.
I have transitioned into the data domain to focus on building modern data platforms, cloud data pipelines, and analytics solutions, applying strong engineering principles to deliver production-ready, business-driven data systems.
I am currently engaged as an Independent Data Engineering & Analytics Consultant, building industry-ready, end-to-end data solutions with a strong focus on cloud data platforms, scalable pipelines, and business analytics.
These projects are designed to mirror real-world enterprise data platforms, focusing on scalability, data quality, and analytics consumption for business decision-making.
🔗 https://github.com/AmeeJoshi-MCA/azure-databricks-end-to-end-retail-lakehouse
Enterprise-style Azure Databricks Lakehouse built using Medallion Architecture (Bronze–Silver–Gold), featuring incremental ingestion, Delta Lake transactional modeling, SCD Type 1 & 2 dimensions, append-only fact tables, and analytics-ready datasets for retail BI and reporting.
🔗 https://github.com/AmeeJoshi-MCA/azure-end-to-end-data-engineering-adventure-works
Production-style Azure data engineering solution using ADF, ADLS Gen2, Databricks, and Synapse to deliver metadata-driven ingestion, Medallion Architecture processing, and analytics-ready datasets optimized for BI and enterprise reporting.
🔗 https://github.com/AmeeJoshi-MCA/SQL-Server-DataWarehouse-and-Analytics
Built Medallion-layered Star Schema in SQL Server. Optimized T-SQL ETL pipelines to create a Single Source of Truth for advanced analytics & high-performance BI reporting.
🔗 https://github.com/AmeeJoshi-MCA/Bank-Loan-Analysis
Engineered an ETE risk reporting analyzing loan performance, risk indicators, and KPIs, using SQL, Python, and Power BI , tableau, Excel. Automated KPI tracking and loan segmentation to drive data-driven financial risk assessments.
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Spotify End-to-End Azure Data Engineering Pipeline
🔗 https://github.com/AmeeJoshi-MCA/Spotify-EndToEnd-Azure-Data-Engineering-Pipeline
Deployed a production-grade Azure Lakehouse via Databricks Asset Bundles (DABs). Utilized Delta Live Tables, CDC, and ADF watermarking to ensure scalable, ETE incremental data processing and security. -
Azure Data Engineering Framework – Dynamic Ingestion
🔗 https://github.com/AmeeJoshi-MCA/Azure-Data-Engineering-Framework-Dynamic-Ingestion
Metadata-driven ingestion framework with reusable, dynamic pipelines built on Azure. -
Enterprise Data Engineering with Azure Data Factory
🔗 https://github.com/AmeeJoshi-MCA/Azure-data-factory-enterprise-data-engineering
Implemented a modular ADF ingestion framework for enterprise scales. Developed metadata-driven pipelines, REST API pagination, and delta loads, integrating Logic App alerts and GitHub CI/CD. -
AdventureWorks Excel Sales Analytics Dashboard
🔗 https://github.com/AmeeJoshi-MCA/AdventureWorks-Excel-Sales-Analytics-Dashboard
AdventureWorks Analysis: Built a professional BI suite in Excel using Power Query and Power Pivot. Developed DAX-driven star schemas and interactive dashboards to track YoY growth and customer profitability. -
Spotify User Behavior Analytics (Power BI)
🔗 https://github.com/AmeeJoshi-MCA/Spotify-User-Behavior-Analytics-PowerBI
Created a Power BI suite featuring Heat Maps and Quadrant Analysis. Developed complex DAX measures and star schemas to analyze 11 years of user behavior and engagement metrics. -
Social Media Ad Performance Analytics
🔗 https://github.com/AmeeJoshi-MCA/Social-Media-Ad-Performance
Architected a Power BI marketing suite using SQL and DAX. Optimized ad spend by analyzing funnel metrics (CTR, Conversion, ROI) across demographics for data-driven campaign scaling. -
Blinkit-Analysis
🔗 https://github.com/AmeeJoshi-MCA/Blinkit-Analysis
Executed a full SQL-Python-BI pipeline to optimize inventory and sales. Developed statistical models and Power BI reports to identify operational inefficiencies and revenue drivers.
- Cloud & Data Platforms: Azure (Synapse Analytics, Databricks, ADF, ADLS Gen2, Unity Catalog)
- Data Engineering: ETL / ELT Pipelines, Medallion Architecture (Bronze–Silver–Gold), Lakehouse Architecture, Data Modeling, Data Quality & Validation
- Analytics & BI: Power BI, Tableau, Excel (Power Pivot), Financial KPIs
- Engineering Practices: Git, GitHub, Version Control, Modular Pipeline Design, Documentation
Primary focus on Azure-based data platforms, with cloud-agnostic data engineering principles applicable across environments.
Data-focused roles such as:
- Data Engineer
- Azure Data Engineer
- Analytics Engineer
- Cloud Data Engineer
- Data Platform Engineer
- Data Analytics Engineer
🔗 LinkedIn: https://www.linkedin.com/in/amee-joshi-09b77754/
💻 GitHub: https://github.com/AmeeJoshi-MCA
⭐ Thank you for exploring my portfolio. This portfolio reflects my hands-on experience building scalable, analytics-ready data platforms with real-world engineering and business context.