• 🔧  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 | Solicitor General
• 📺  YouTube  youtube.com/@DataToCrunch
• 💬  LinkedIn  linkedin.com/in/rutujabkadam
• 📍  Toronto, Ontario, Canada

I'm a Data Engineer and Analytics Practitioner / Educator based in Toronto, building production-grade cloud data pipelines and educating the data community of 10K+ 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
• Databricks — PySpark, Spark SQL, Delta Live Tables (Lakeflow), Medallion Architecture, Auto Loader, Lakeflow Connect, Unity Catalog, Lakehouse Federation, SCD Type 1 & 2, CDC, Watermarking, Jobs & orchestration, Databricks SQL, SQL Warehouses, Databricks Dashboards, Genie / AI-BI dashboards, SQL Editor, Alerts, query optimization
• Snowflake — Snowpipe, SnowSQL, Snowsight UI & Dashboard, Storage & Notification Integration, COPY INTO, Streams & Tasks, Stored Procedures, Dynamic Tables, Standard/Transient/Temporary Tables, structured data, semi-structured data (JSON, XML, Variant), Secure Views, Sequences, Resource Monitors, Clustering Keys, Time Travel, Zero-Copy Cloning, Data Sharing & Reader Accounts, Streamlit Apps/Dashboards, Alerts, DEV/PROD environments, star/snowflake schemas, fact/dimension tables, SCD Type 1 & 2, CDC
• Microsoft Fabric — Lakehouses, Warehouses, Dataflows Gen2, Notebooks (PySpark/Spark SQL), Pipelines (Data Factory), Eventstream, Eventhouse (KQL), Real-Time Intelligence, Activator, Shortcuts, Mirroring, OneLake, Fabric Environments, Deployment Pipelines, Git Integration/CI-CD, Workspace & Capacity Management, Row/Object/Column-Level Security, Direct Lake Semantic Models, Import/DirectQuery modes, DAX Measures, Calculation Groups, Field Parameters, Star Schema Design, Aggregations, Performance Optimization (VACUUM, OPTIMIZE, partitioning), Pipeline & Spark Monitoring, Power BI Reports & Copilot
• Data Modeling & Governance — Star & Snowflake Schema, Fact & Dimension tables, Unity Catalog, Secure Views, Row-Level/Object-Level/Column-Level Security, Fabric Workspace Roles & Item-Level Permissions
• BI & Visualization — Power BI, Tableau, Databricks SQL dashboards, Streamlit Apps
• DevOps — GitHub, Azure DevOps

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.

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

Core expertise: Microsoft Fabric (Lakehouses, Warehouses, Dataflows Gen2, Notebooks, Pipelines, Eventstream, Eventhouse/KQL, Real-Time Intelligence, Activator, Shortcuts, Mirroring, OneLake, Direct Lake, RLS/OLS/CLS, Git Integration & Deployment Pipelines) · Azure Data Factory · ADLS Gen2 · Azure Synapse Analytics · Azure Event Hub · Azure Key Vault · Databricks (PySpark, Spark SQL, Delta Live Tables/Lakeflow, Lakeflow Connect, Auto Loader, Unity Catalog, Lakehouse Federation, Watermarking, Jobs & Orchestration, Databricks SQL, SQL Warehouses, Dashboards, Genie/AI-BI, SQL Editor, Alerts, query optimization) · Snowflake (Snowpipe, SnowSQL, Snowsight, Storage & Notification Integration, COPY INTO, Streams & Tasks, Stored Procedures, Dynamic Tables, Secure Views, Sequences, Resource Monitors, Clustering Keys, Time Travel, Zero-Copy Cloning, Data Sharing & Reader Accounts, Streamlit Apps) · Medallion Architecture · Star & Snowflake Schema · Fact & Dimension Tables · SCD Type 1 & 2 · CDC · Power BI (DAX, Calculation Groups, Field Parameters) · Tableau · T-SQL · GitHub · Azure DevOps · CI/CD