CB Chandra Kanth Boga.Azure Data Engineer Let's connect
Open to Azure data engineering opportunities

AZURE · DATABRICKS · MICROSOFT FABRIC

Building reliable data platforms
from source to insight.

I design lakehouse architectures and scalable data pipelines using Azure Databricks, Microsoft Fabric, PySpark, and SQL—turning complex data into trusted, analytics-ready products.

Explore my work Request résumé
LakehouseArchitecture
Batch + StreamData pipelines
GovernedAnalytics data

PLATFORM BLUEPRINT

Lakehouse flow

DESIGN
Sources
01BRONZERaw ingestion
02SILVERClean & conform
03GOLDBusiness ready
Insights
Delta LakeUnity CatalogQuality checks
AZURE DATABRICKS◆MICROSOFT FABRIC◆ PYSPARK◆DELTA LAKE◆DATA FACTORY

TECHNICAL EXPERTISE

A modern Azure data stack.

Tools and patterns for dependable ingestion, transformation, governance, orchestration, and analytics.

Lakehouse engineering

Azure Databricks

  • Delta Lake
  • Unity Catalog
  • Auto Loader
  • Workflows

Unified analytics

Microsoft Fabric

  • OneLake
  • Lakehouse
  • Data Factory
  • Power BI

Cloud foundations

Azure Data Platform

  • ADLS Gen2
  • Azure Data Factory
  • Key Vault
  • Event Hubs

Code & modeling

Engineering

  • Python
  • PySpark
  • SQL
  • Dimensional Modeling

SELECTED PROJECTS

Data engineering in practice.

Replace these starter case studies with your GitHub repositories, architecture diagrams, and measurable outcomes.

01

DATABRICKS

Retail Lakehouse Pipeline

A metadata-driven medallion pipeline that incrementally ingests JSON data, validates quality, and publishes analytics-ready Delta tables.

Auto LoaderDelta LakePySparkUnity Catalog
ARCHITECTUREBronze → Silver → Gold View case study
02

MICROSOFT FABRIC

Sales Analytics Platform

An end-to-end Fabric solution connecting OneLake, notebooks, a semantic model, and Power BI for governed self-service reporting.

FabricOneLakeData FactoryPower BI
ARCHITECTURESource → Insight View case study
03

REAL-TIME DATA

Streaming Operations Monitor

A streaming architecture that processes event data, applies windowed transformations, and surfaces operational metrics.

Event HubsStructured StreamingDeltaSQL
ARCHITECTUREEvents → Live KPIs View case study

ABOUT ME

Engineering discipline, applied to data.

I bring an engineering mindset to the cloud: understand the requirement, design for reliability, test the edge cases, and make the result easy to operate. My current focus is building production skills across Azure Databricks and Microsoft Fabric.

I enjoy translating business questions into maintainable data models and pipelines that analysts and decision-makers can trust.

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LEARNING & CREDENTIALS

DP-700
Fabric Data EngineerLearning path
AZURE
Azure Data EngineeringCore platform
DBX
Databricks LakehouseCore focus
CURRENTLY EXPLORINGFabric · Databricks · CI/CD

LET'S BUILD SOMETHING USEFUL

Have a data challenge in mind?

I'm interested in Azure data engineering opportunities, collaborative projects, and conversations about modern lakehouse architecture.

boga.chandrakanth@gmail.com LinkedIn GitHub