Hello! 

I’m Madhur Jain, a Data Engineering and Analytics Engineering professional focused on building scalable, governed, and high-performance data platforms that deliver measurable business impact. I design end-to-end analytics systems that help organisations reduce operational costs, shorten decision cycles, improve data reliability, and scale analytics with confidence.

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I specialise in transforming complex, multi-source data—structured, semi-structured, and unstructured—into unified, analytics-ready models. By applying strong analytics-engineering principles, I standardise business logic, eliminate metric inconsistencies, and create curated data layers that reduce downstream rework and accelerate insights.

 

My work is business-first and engineering-led. Using Microsoft Fabric, Azure Data Factory, SQL and PySpark, I build automated, fault-tolerant pipelines and Lakehouse architectures with clear Bronze, Silver, and Gold layers, optimised for performance, governance, and cost efficiency.

 

On top of these platforms, I enable decision-making through Power BI, delivering performant semantic models and reports built on trusted data foundations—helping stakeholders identify inefficiencies, manage risk, and act faster with confidence.

 

Core Capabilities

I build end-to-end data engineering solutions using Microsoft Fabric, including:

• Designing Lakehouse architectures using Bronze, Silver, and Gold layers

• Developing incremental and batch data pipelines using Fabric pipelines and notebooks

• Transforming and optimising data using PySpark and SQL

• Modeling analytics-ready datasets for Power BI and downstream consumption

• Implementing data quality checks and monitoring to ensure reliable pipelines

• Optimising data workflows for performance and cost efficiency

 

I build data platforms that scale with the business—engineered for performance, governed for trust and designed to deliver measurable impact.​​

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