Data Engineering Expertise
Expert in designing and implementing large-scale data systems that handle complex data flows, distributed architectures, and real-time processing. With years of experience processing terabytes of data from 100s of global sensors and creating ETL pipelines for complex data workflows, I specialize in building robust, scalable infrastructure.
My approach combines cloud-native architectures (Kubernetes, serverless), event-driven design patterns, and comprehensive monitoring to create systems that are both performant and maintainable.
What I Offer
Technical Stack
Cloud Platforms
- Azure
- AWS
- Google Cloud
Data Processing
- Apache Spark
- PySpark
- Pandas
- ETL Pipelines
Orchestration
- Kubernetes
- Airflow
- Docker
- CI/CD Pipelines
Databases
- PostgreSQL
- MongoDB
- SQL Server
- Cosmos DB
APIs & Frameworks
- REST APIs
- FastAPI
- Terraform
- Infrastructure as Code
Professional Background
Expertise & Specialization
Specialized in cloud-native architecture, distributed systems, and ETL pipeline design. Expert at designing systems that process massive volumes of data reliably and efficiently while maintaining high availability and fault tolerance.
Key Achievements
• Architected systems processing 100+ global data streams handling terabytes of data
• Delivered 50% performance improvements through Kubernetes-based infrastructure optimization
• Built monitoring systems ensuring 99.9% data reliability and uptime for mission-critical operations
Data Pipeline Demo
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