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rutujak-git/README.md

Hi 👋, I'm Rutuja Kadam

Data Engineer & Data Analytics Practitioner | Azure Services · Databricks · Snowflake | Toronto, Canada

LinkedIn YouTube GitHub Email


I build end-to-end cloud data pipelines that transform raw, complex data into structured, reliable, analytics-ready datasets. My work spans Azure Services, Databricks, Snowflake, & BI tools — from ingestion and transformation to governance, orchestration, and BI delivery. I am passionate about clean data architecture and sharing that knowledge through my YouTube channel, DataToCrunch.


Girl Working on Data

  • 🔧  Data Engineer & Analytics Practitioner — cloud-native pipelines & Lakehouse architecture
  • 🏢  3.5+ years of enterprise experience at Accenture (SAP IS-U & SAP CRM)
  • 🎓  PG Diploma in Business Insights & Analytics — Humber College, Canada
  • 🏛️  Co-op Data Analyst — Ontario Public Service
  • 📺  YouTube  youtube.com/@DataToCrunch
  • 💬  LinkedIn  linkedin.com/in/rutujabkadam
  • 📍  Toronto, Ontario, Canada


🧠 About Me

I'm a Data Engineer and Analytics Practitioner / Educator based in Toronto, building production-grade cloud data pipelines and educating the data community of 8K+ members through my YouTube channel DataToCrunch.

My foundation comes from 3.5+ years at Accenture, where I worked as an Application Development Associate & Application Development Analyst on enterprise-scale SAP IS-U and SAP CRM projects. I contributed across the full SDLC — from system analysis, enhancement development, and debugging, to testing, deployment support, and production incident resolution. Collaborating with global stakeholders on high-priority deliverables gave me a strong understanding of how data flows and behaves at enterprise scale.

Afterwards I completed my 2 years postgraduate program in Business Insights & Analytics at Humber College where I learned Python, SQL, Machine Learning, Predictive Analysis, Power BI, and Tableau. I applied my skills during a Co-op at the Ontario Public Services | Solicitor General, where I built advanced Power BI dashboards — implementing DAX measures, time intelligence, row-level security (RLS), and full database integration.

Today, I independently design and implement end-to-end data pipelines using the modern cloud data stack:

  • Azure — Azure Data Factory (parameterized, event-driven & incremental pipelines), Azure SQL Database, ADLS Gen2, Azure Synapse Analytics, Azure Databricks, Azure DevOps, Azure Logic Apps, Azure Key Vault
  • Databricks — PySpark, Spark SQL, Delta Live Tables (DLT-streaming tables, materialized views), Medallion Architecture (Bronze/Silver/Gold), Auto Loader, Lakeflow Connect, SCD Type 1 & 2, CDC, Watermarking, Unity Catalog, Lakehouse Federation, Jobs & orchestration
  • Snowflake — Snowpipe,SnowSQL,Snowsight UI & Dashboard, COPY INTO, Streams & Tables, semi-structured data (JSON, XML), star/snowflake schemas, fact/dimension tables, clustering keys, Time Travel, zero-copy cloning, SCD Type 2, CDC.
  • Data Modeling & Governance — Star & Snowflake Schema, Fact & Dimension tables, Unity Catalog, Lakehouse Federation, cross-platform queries (Snowflake · Azure Synapse · Azure SQL), Row-Level Security
  • BI & Visualization — Power BI, Tableau, Databricks SQL dashboards
  • DevOps — GitHub, Azure DevOps, CI/CD pipelines

Every project I build is designed from scratch and published end-to-end on my channel to help data enthusiasts learn real-world engineering practices.


🚀 Featured Projects

💡 All projects below were built from scratch and published as full tutorials on YouTube @DataToCrunch

# Project Description Stack YouTube
1 AdventureWorks Azure ETL + Unity Catalog End-to-end ETL pipeline using AdventureWorks2022 dataset — SSMS, Azure SQL DB, ADF, ADLS Gen2, Databricks Unity Catalog & Power BI ADF · Databricks · Unity Catalog · Power BI ▶ Watch
2 Amazon Prime Data Pipeline Medallion Architecture pipeline with HTTP ingestion via ADF, PySpark transformations & ADLS Gen2 on Amazon Prime Movies & TV Shows dataset ADF · PySpark · ADLS Gen2 · Power BI ▶ Watch
3 Databricks Delta Lake ETL ETL pipeline with Unity Catalog, Medallion Architecture (Bronze/Silver/Gold) & Delta Lake optimization techniques ADLS Gen2 · Databricks · Delta Lake · Unity Catalog · Python · Databricks Dashboard ▶ Watch
4 Banking DLT Pipeline — PySpark Automated banking ETL with Auto Loader, Delta Live Tables, data quality Expectations & SCD Type 1 & 2 Databricks Lakeflow Declarative Pipeline · Auto Loader · Python · Jobs · Dashboard ▶ Watch
5 Banking DLT Pipeline — SQL SQL-based Delta Live Tables pipeline with automated ingestion, quality enforcement & orchestration Databricks Lakeflow Declarative Pipeline · Auto Loader · SQL · Jobs · Dashboard ▶ Watch
6 E-Commerce Incremental Pipeline Incremental processing with SCD Type 2, Watermark logic, Lakehouse Federation & Delta MERGE operations Databricks · Lakehouse Federation · Python ▶ Watch
7 AdvantureWorks Azure ETL Pipeline Extract on-prem SQL Server data using Azure Data Factory, transform with Databricks, model in Synapse, and create dashboards in Power BI SSMS · Databricks · Data Factory · Synapse ·Power BI ▶ Watch
8 FlowBridge Snowflake Data Pipeline Build a complete production-ready end-to-end data pipeline on Snowflake Snowflake · Azure · Streamlit · Snowpipe ▶ Watch

🛠️ Languages and Tools

Azure    Databricks    Snowflake    Python    Apache Spark    Power BI    Tableau    SQL Server    MySQL    PostgreSQL    Git    Azure DevOps

Core expertise: Azure Data Factory · ADLS Gen2 · Azure Synapse Analytics · Databricks Lakeflow Connect · Delta Live Tables · Medallion Architecture · PySpark · Spark SQL · Delta Lake · Auto Loader · Unity Catalog · Lakehouse Federation · Automated Lakeflow Declarative Pipeline · SCD Type 1 & 2 · CDC · Watermarking · Snowflake · Snowpipe · Star/Snowflake Schema · Fact & Dimension Tables · Power BI · Tableau · GitHub · Azure DevOps · CI/CD


🏅 Certifications

Certification Issuer Link
🎖️ Microsoft Certified: Power BI Data Analyst Associate (PL-300) Microsoft View
🎖️ Microsoft Certified: Azure Data Fundamentals (DP-900) Microsoft View
🎖️ Databricks Certified Data Engineer Associate Databricks View
🎖️ Rutuja Bhagatsing Kadam : Databricks & Snowflake Credentials wallet Databricks View
🎖️ Rutuja Bhagatsing Kadam : Microsoft Credentials Wallet Databricks View
🎖️ Azure Databricks Data Engineer Associate(Beta) Microsoft View
🎖️ Databricks Certified Data Analyst Associate Databricks View
🎖️ SnowPro Associate: Platform Certification Snowflake View
🎖️ Microsoft Certified: Fabric Data Engineer Associate Microsoft [Scheduled]
🎖️ Microsoft Certified: Fabric Analytics Engineer Associate Microsoft [Scheduled]

🎓 Education

Degree Institution Year
PG Diploma — Business Insights & Analytics Humber College, Canada 2021 – 2023
B.E. — Electronics & Telecommunication Engineering Smt. Kashibai Navale College of Engineering, Pune University 2013 – 2017

Pinned Loading

  1. AdventureWorks-Azure-ETL-UnityCatalog-Lakehouse AdventureWorks-Azure-ETL-UnityCatalog-Lakehouse Public

    End-to-end Azure Data Engineering project from scratch using AdventureWorks2022 dataset, implementing full ETL pipeline with SSMS,Azure SQL DB, ADF, ADLS Gen2, Databricks (Unity Catalog), and Power…

    Jupyter Notebook

  2. Azure-Data-Pipeline-AmazonPrimeDataset-adf-adlsgen2-databricks-powerbi Azure-Data-Pipeline-AmazonPrimeDataset-adf-adlsgen2-databricks-powerbi Public

    End-to-end data engineering pipeline using Azure Data Factory (HTTP ingestion), Azure Databricks (PySpark), and ADLS Gen2 implementing Medallion Architecture on the Amazon Prime Movies & TV Shows d…

  3. Azure-Databricks-UnityCatalog-DeltaLake-ETL-Pipeline Azure-Databricks-UnityCatalog-DeltaLake-ETL-Pipeline Public

    An end-to-end Azure Data Engineering project demonstrating an ETL pipeline using Databricks Unity Catalog, Medallion Architecture (Bronze, Silver, Gold), and Delta Lake optimization techniques.

    Python

  4. databricks-lakeflow-banking-dlt-pyspark databricks-lakeflow-banking-dlt-pyspark Public

    Automated Banking ETL Pipeline using Databricks Lakeflow (DLT) and Python. Features incremental ingestion via Auto Loader, data quality enforcement (Expectations), and SCD Type 1 & 2 for historical…

    Python

  5. databricks-lakeflow-banking-dlt-sql databricks-lakeflow-banking-dlt-sql Public

    Production-ready Banking ETL Pipeline built on Databricks using SQL-based Lakeflow Declarative Pipelines (Delta Live Tables). Features automated ingestion via Auto Loader, data quality enforcement …

  6. databricks-lakehouse-ecommerce-incremental-pipeline databricks-lakehouse-ecommerce-incremental-pipeline Public

    End-to-end E-commerce Data Pipeline built on Databricks using Lakehouse Federation, Watermark logic, and Medallion Architecture. Features incremental processing (SCD Type 2), Delta Lake MERGE opera…

    Python