I am a results-driven Data Engineer with a proven track record of architecting scalable data platforms that convert complex datasets into actionable business intelligence. At BGC (Australia) Pty Ltd, I led the modernisation of data pipelines across Microsoft Fabric, Azure Data Factory, and Apache NiFi—achieving a 40% reduction in batch processing time and significantly improving time-to-insight.
My recent initiatives include building a cost-efficient data lakehouse leveraging Apache Kafka, Hadoop, and Snowflake—delivering 30% infrastructure savings while maintaining enterprise-grade auditability and compliance standards. I excel at bridging the gap between technical execution and strategic objectives, mentoring high-performing teams, and collaborating cross-functionally to deliver business-aligned data solutions.
Fluent in English, Hindi, and Punjabi, I work effectively across diverse, cross-cultural teams. I’m also deeply engaged with emerging technologies such as Agentic AI and large language models, exploring their potential to revolutionize decision-making and unlock competitive advantage through autonomous data-driven systems.
Design scalable, secure data platforms and pipelines from ingestion to consumption, delivering real‑time insights and strategic value.
Implement robust governance frameworks, elevating data quality and compliance while maintaining lineage and auditability.
Architect and optimise cloud‑native data solutions on Azure, AWS and Snowflake, delivering cost‑effective scalability and performance.
Confluent certification demonstrating proficiency with Apache Kafka and streaming data pipelines. Credential ID 153657031. Issued Jun 2025 – Expires Jun 2027.
Snowflake credential validating expertise in Snowflake architecture, data warehousing and cloud data engineering. Credential ID 144446911. Issued May 2025 – Expires May 2027.
Completed multi‑course specialisations on Coursera and edX covering self‑driving cars, natural language processing, TensorFlow and time‑series prediction from the University of Toronto and DeepLearning.AI. Demonstrates solid foundations in machine learning and deep learning.
Certified across Azure (AI Fundamentals, Data Fundamentals, Fabric Analytics Engineer and Data Scientist Associate), AWS (Fundamentals, Security, Migration, Serverless & Cloud‑Native) and Google Cloud machine‑learning programmes, demonstrating versatile cloud data expertise.
Skilled in dbt fundamentals and a variety of data science and programming courses including Python programming, geospatial analysis, database design, WordPress site development and more—equipping me to deliver end‑to‑end data solutions.
Senior Data Engineer at INX Software (Mentor)
Madhur’s drive and passion for data science are unmatched. His facial‑recognition project for INX Hack Day 2022 won the Most Innovative prize.
Utilities Engineer & Deputy Manager
A great motivator and exemplary senior who shares knowledge generously. Working with Madhur has been an inspiring learning experience.
Professor & Director, Centre for Applied AI
Madhur’s pristine work ethic and adaptability stood out in my classes at Macquarie University. He goes out of his way to help others.
Program Director & Senior Lecturer, Macquarie University
Knowledgeable, articulate and hardworking, Madhur brought integrity and intelligence to every task during his Master’s programme.
Business Analyst & Data Analyst
Multi‑talented and enthusiastic, he’s always eager to learn and implement new technologies and to lend a helping hand.
Director of Education, Macquarie University
One of the hardest‑working students I’ve taught; Madhur combines perseverance with honed analytical skills to achieve great results.
Pre‑owned Vehicle Ecosystem Leader
A tech geek with an innovative mind and a gifted writer, he’s equipped with the right tools and mindset to excel.
Full‑Stack Developer
Can step into any area and conquer it; always learning new technologies and ready to support others.
I'm currently open to both freelance and full-time opportunities. I specialize in building modern data solutions—from pipelines and lakehouses to real-time dashboards and AI integrations.
Interested in collaborating or discussing data engineering challenges? Feel free to reach out.