I design and build governed lakehouse platforms that turn raw enterprise data into trusted products for analysts, data scientists, and BI consumers. Twelve years across the stack — from hand-rolled Python/SQL pipelines to medallion lakehouses on Databricks and Microsoft Fabric, with GenAI/RAG serving layers on top.
- 🏗️ Currently: Asst. Director, Data Engineering @ Moody's — architecting Databricks & Fabric data platforms
- 🔭 Focus: Databricks (Delta, Unity Catalog, Mosaic AI), Microsoft Fabric / OneLake, medallion architecture, data quality & governance
- 🎓 B.Tech CSE (JNTU Anantapur) · MBA Finance (Sri Venkateswara University)
- 📍 Bangalore, India · 📚 perpetual learner
A progressive portfolio, from early pipelines to today's lakehouse + GenAI platforms:
| Year | Project | Stack |
|---|---|---|
| 2026 | Enterprise Lakehouse on Microsoft Fabric | Fabric · OneLake · Direct Lake · medallion |
| 2025 | Financial-Research RAG on Databricks | Mosaic AI Vector Search · MLflow · model serving |
| 2023 | Grant-Data Integration Pipeline | Databricks · PySpark · Delta · Great Expectations |
| 2022 | Customs & Trade Analytics Lakehouse | Databricks · Unity Catalog · medallion |
| 2021 | Platform-Usage Analytics | Azure (ADF · Synapse · ADLS) · Power BI |
| 2019 | Yield-Curve Outlier Detection | AWS · Streamlit · Terraform |
| 2018 | Predictive Error RCA Pipeline | Python · NLP feature engineering |
| 2016 | Market-Performance Feature Platform | Python · point-in-time datasets |
| 2014 | Structured-Finance Pricing Pipeline | Python · SQL |
Lakehouse & Data Platforms
Databricks Delta Lake Unity Catalog Microsoft Fabric Apache Spark PySpark
GenAI & ML
Cloud
Azure Azure Data Factory Azure Synapse AWS
Languages
Orchestration, Quality & IaC
Apache Airflow Great Expectations Terraform
BI & Visualization
Databases & Storage
Dev & Ops
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