🚀 Passionate about building scalable data platforms, distributed ETL pipelines, and cloud-native healthcare data solutions.

• 💼 3.5+ years of experience in Data Engineering
• ⚡ Specialized in PySpark, Apache Spark, SQL & ETL Pipelines
• 🏥 Experience building FHIR-compliant healthcare data systems
• ☁️ Working with AWS, Iceberg, Data Lakes & Distributed Processing
• 📍 Based in India | Open to opportunities across India
• 🌐 Portfolio: https://sharu2172.github.io/
• 📫 Reach me at: [email protected]

I am a results-driven Data Engineer with hands-on experience designing scalable ETL systems, optimizing distributed data workflows, and transforming large-scale healthcare datasets into analytics-ready formats.

My work primarily focuses on:

• Building high-performance PySpark pipelines
• Data lake & Apache Iceberg implementations
• Distributed computing optimization
• Healthcare interoperability (FHIR)
• Cloud-native data engineering workflows
• Data quality, governance, and transformation

I enjoy solving complex data engineering problems and building systems that enable analytics, reporting, and data-driven decision-making at scale.

• Python
• SQL
• Java
• PL/SQL
• Bash

• Apache Spark
• PySpark
• Hadoop Ecosystem
• Apache Iceberg
• Kafka (Foundational)
• dbt (Foundational)

• AWS S3
• AWS Glue
• AWS Lambda
• Docker
• MinIO

• MySQL
• SQL Server
• MongoDB
• Data Lakes
• Data Warehouses
• Parquet
• CSV

• FastAPI
• REST APIs
• CLI Automation

• ETL / ELT Pipeline Design
• Data Modeling
• Data Governance
• Data Validation & Quality
• Agile Development
• Performance Optimization

📅 Aug 2022 – Apr 2026

• Designed scalable PySpark ETL pipelines for healthcare datasets
• Built CLI-based automation tools for distributed processing
• Processed large-scale healthcare data into Apache Iceberg tables
• Improved Spark job performance by optimizing partitioning & caching strategies
• Developed FHIR-compliant transformation workflows
• Collaborated with analytics & engineering teams on data-driven solutions

Python PySpark SQL Server FHIR Iceberg MinIO

Built a production-grade healthcare ETL pipeline for Pennstate Health that:

• Processes large-scale healthcare datasets
• Converts data into FHIR-compliant formats
• Stores transformed datasets in a scalable data lake architecture
• Improves interoperability and analytics readiness
• Ensures healthcare data standard compliance

• Distributed ETL architecture
• Spark-based large-scale processing
• Healthcare interoperability implementation
• Data lake optimization

Python FastAPI SQL Healthcare Data

Developed a hospital price transparency aggregation platform that:

• Aggregates healthcare pricing information
• Enables cost comparison for treatments
• Provides a user-facing FastAPI web application
• Helps consumers identify affordable healthcare options
• Supports compliance with transparency regulations

• Advanced Data Engineering
• Distributed Systems
• Cloud-Native Data Platforms
• Data Lakehouse Architectures
• Real-time Data Processing
• AI-powered Data Workflows
• Workflow Automation using n8n & AI Agents

• Portfolio: https://sharu2172.github.io/
• GitHub: https://github.com/Sharu2172
• LinkedIn: https://linkedin.com/in/d-sharath-a6289b152
• Email: [email protected]

I enjoy building automation systems, AI workflows, and scalable data platforms that solve real-world engineering challenges.