💼 About Me

I’m Harish C, a data engineer dedicated to building scalable, reliable, and future-ready data ecosystems.

My experience spans designing and optimizing end-to-end data platforms across industries, where I focus on:

• Distributed data processing with PySpark & Spark SQL
• Lakehouse architectures built on Databricks & Delta Lake
• Workflow orchestration using Airflow & dbt
• Cloud-native warehousing with Snowflake
• Data quality, lineage, observability & cost governance

I specialize in turning complex data systems into high-performance, production-grade architectures that balance speed, reliability, and cost-efficiency.

🧩 What Drives My Work

My philosophy is simple:

Data engineering should be an engineering discipline — not just pipeline writing.​

I believe in:

• Architecting for scale, not patching for survival
• Designing systems with clarity and intent
• Making performance predictable
• Building data platforms that teams can trust
• Creating solutions that grow with the business

I love breaking down even the most advanced concepts into something clear, practical, and rooted in real engineering principles.

🛠️ Technical Strengths

Core Expertise​

• PySpark, Spark SQL
• Databricks Lakehouse & Delta Lake
• Snowflake Architecture
• Airflow & dbt
• Streaming & event-driven patterns
• Data modeling & warehouse optimization

Cloud Platforms​

• Azure
• Google Cloud Platform
• Serverless data services

Engineering Focus​

• Performance tuning
• Reliability engineering
• Data governance & observability
• Platform automation
• Cost optimization

🤝 Final Note

If you value clarity, precision, and real-world data engineering,
you’re in the right place.

My work — and this platform — reflects one mindset:

**Build systems that last.​

Explain concepts that stick.
Engineer solutions that scale.**

— Harish C