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WHO I AM
Data Engineer focused on building scalable Lakehouse and MLOps foundations on Azure. With hands-on experience in Databricks, Spark Structured Streaming, Delta Lake, and Synapse, I deliver reliable batch and real-time pipelines that power enterprise analytics.
I've implemented automated deployments with Terraform + Azure DevOps and built strong data quality, governance, and monitoring systems using Unity Catalog, Great Expectations, and Azure Monitor.
My expertise extends to building end-to-end MLOps workflows with MLflow, feature stores, drift detection, and retraining pipelines, plus a multimodal RAG agent for document intelligence.
Lakehouse Architecture
Expert in Medallion (Bronze/Silver/Gold) architecture for data lineage and governance
Azure Ecosystem
Deep expertise in Azure Data Factory, Synapse, Databricks, and ADLS Gen2
MLOps & AI
Building end-to-end ML workflows with MLflow, feature stores, and drift detection
Real-time Pipelines
Spark Structured Streaming for reliable batch and real-time data processing
TECHNICAL SKILLS
Languages
Cloud Platforms
ETL & Orchestration
DataOps & CI/CD
Data Quality & Governance
Databases
ML/AI Tools
PROFESSIONAL EXPERIENCE
Senior Data Engineer
- ▸Built the Lakehouse platform using Databricks, Spark, and Delta Lake with Medallion (Bronze/Silver/Gold) architecture for data lineage and governance
- ▸Developed and optimized ETL pipelines for batch and streaming data using Python, PySpark, and Spark Structured Streaming
- ▸Automated CI/CD pipeline deployments and infrastructure provisioning with Terraform and Azure DevOps
- ▸Implemented data quality monitoring and observability using Great Expectations, Azure Monitor, and custom SLA/SLO alerting frameworks
- ▸Optimized Spark performance through Z-ordering, file clustering, and partitioning strategies on Parquet/Delta formats
- ▸Used PySpark MLlib and MLflow in Databricks to train and deploy classification and clustering models for customer segmentation and churn prediction
- ▸Built and maintained a feature store in Unity Catalog/Delta tables to serve consistent features to training and production ML pipelines
Data Engineer
- ▸Designed Azure Data Factory ETL pipelines to ingest data from multiple transactional systems into Azure Synapse dedicated SQL pools
- ▸Built Azure Functions to validate incoming files, update metadata tables, and trigger downstream processing
- ▸Orchestrated end-to-end data ingestion and transformation workflows using Azure Data Factory pipelines and Azure Logic Apps
- ▸Leveraged Azure Synapse serverless SQL and Azure Data Lake Storage for on-demand querying over large datasets
- ▸Implemented monitoring and alerting with Azure Monitor, Log Analytics, and action groups to track ETL pipeline health
- ▸Collaborated with BI teams to deliver Power BI dashboards on certified Azure Synapse and Data Lake datasets
KEY PROJECTS
Azure MLOps & Data Lakehouse
Built automated MLOps framework with Medallion architecture on ADLS Gen2, processing NYC taxi data. Implemented Delta Lake ACID transactions ensuring data integrity and optimized feature serving through Synapse Serverless SQL views.
- ▸Medallion architecture (Bronze/Silver/Gold)
- ▸Delta Lake ACID transactions
- ▸Self-healing monitoring with Azure Monitor
- ▸Automated model drift detection and retraining
Multimodal RAG Agent for Document Intelligence
Architected Multimodal RAG system capable of querying unstructured PDFs containing text, hierarchical tables, and visual charts. Engineered Multi-Vector Indexing strategy with ChromaDB, linking text embeddings to visual assets for context-aware retrieval.
- ▸Multi-Vector Indexing strategy
- ▸Context-aware retrieval system
- ▸RAGAS evaluation framework
- ▸Parent Document Retrieval for accuracy
EDUCATION & CERTIFICATIONS
EDUCATION
Master of Science in Data Science
New Jersey Institute of Technology
Bachelor of Technology in Computer Science
Narasaraopeta Engineering College
LET'S CONNECT
Ready to build scalable data solutions? Let's discuss how I can help transform your data infrastructure and drive business value.