Design and build a cloud-native Enterprise Healthcare Data Platform that integrates Electronic Health Records (EHR), Patient Registration, Appointments, Laboratory, Pharmacy, Billing, Insurance Claims, and Clinical Trial data from multiple hospital systems. Implement a modern Medallion Architecture (Bronze, Silver, Gold) using scalable ETL pipelines, Delta Lake, and cloud-native services to perform data validation, SCD Type 1 & 2, incremental processing, audit logging, and data quality checks.

Develop a production-grade Healthcare Revenue & Insurance Analytics Platform that consolidates patient billing, insurance claims, pharmacy transactions, laboratory reports, admissions, and financial data into a centralized cloud data warehouse. Design scalable Lakehouse Architecture with automated orchestration, incremental data ingestion, metadata-driven pipelines, and enterprise data governance. Implement business KPIs, financial reconciliation, revenue analytics, claims processing.

Build a production-grade Clinical Lakehouse Platform by integrating Clinical Trials, Patient Records, Laboratory, Drug Safety, and Manufacturing data from multiple enterprise systems. Orchestrate end-to-end data pipelines using Apache Airflow, process and transform data in Databricks with PySpark, Delta Lake, and the Medallion Architecture (Bronze, Silver, Gold), and publish curated datasets to Snowflake for enterprise analytics and regulatory reporting.

Build a production-ready cloud data platform for a global pharmaceutical company by ingesting clinical trial, patient, laboratory, and drug safety data into Amazon S3. Develop scalable ETL pipelines using AWS Glue, Apache Spark on Amazon EMR, and Apache Airflow for workflow orchestration. Transform curated datasets into Amazon Redshift for regulatory reporting and clinical analytics while implementing data quality, security, metadata management, and performance optimization.

Build an enterprise Retrieval-Augmented Generation (RAG) application that enables users to interact with business documents using natural language. Develop Delta Live Tables pipelines for document ingestion, generate embeddings with Databricks Vector Search, and deploy a context-aware Question & Answer system using Model Serving. Implement governance, monitoring, and secure access using Unity Catalog and Lakehouse Monitoring to deliver a scalable enterprise AI solution.

Develop a production-grade AI platform by combining an MCP-enabled AI Agent with AI/BI Genie to automate enterprise workflows and provide natural language analytics. Integrate Large Language Models with Databricks, enable intelligent tool calling, automate business processes, and generate AI-powered insights while implementing enterprise governance, monitoring, and secure data access through Unity Catalog.