I am a Data Engineer focused on designing and building scalable, production-style data engineering solutions using Azure and Databricks.
I work on end-to-end data pipelines, Lakehouse architecture, real-time streaming solutions, data quality frameworks, and analytics-ready data platforms.
- 🔹 Azure Data Engineering & Lakehouse Architecture
- 🔹 ETL / ELT Pipeline Development
- 🔹 Batch & Real-Time Data Processing
- 🔹 Databricks & Apache Spark
- 🔹 PySpark & Python Development
- 🔹 Delta Lake & Medallion Architecture
- 🔹 Data Quality & Monitoring
- 🔹 Azure Data Factory Orchestration
- 🔹 SQL & Analytics
- 🔹 Power BI
End-to-end Azure Data Engineering pipeline designed using Azure Data Factory, Databricks, ADLS Gen2, Delta Lake, SQL and Power BI.
Key Areas
- ETL / ELT pipeline design
- Azure Data Factory orchestration
- Databricks transformations
- Delta Lake architecture
- Data quality validation
- Analytics-ready datasets
Production-style e-commerce Lakehouse architecture built using Databricks, PySpark and Delta Lake.
Key Areas
- Medallion Architecture
- CDC processing
- SCD Type 2
- Incremental data processing
- Data quality checks
- Audit monitoring
- Performance optimization
Real-time IoT streaming data engineering project using Databricks, PySpark, Delta Lake and Structured Streaming.
Key Areas
- Structured Streaming
- Event-time processing
- Watermarking
- Window aggregations
- Streaming transformations
- Anomaly processing
- Delta Lake
End-to-end financial fraud and risk analytics Lakehouse designed using Databricks, PySpark and Delta Lake.
Key Areas
- Incremental processing
- Data quality framework
- Risk analytics pipeline
- Medallion Architecture
- Monitoring & auditing
- Pipeline orchestration
Enterprise Databricks Lakehouse implementation using Bronze, Silver and Gold architecture.
Key Areas
- Bronze / Silver / Gold layers
- Data cleansing & transformation
- Data quality validation
- Pipeline orchestration
- Monitoring
- Analytics-ready Gold datasets
I focus on building data platforms that demonstrate practical Data Engineering concepts including:
- Scalable ETL / ELT pipelines
- Lakehouse Architecture
- Medallion Architecture
- Batch & Streaming Processing
- CDC & Incremental Loads
- SCD Type 2
- Data Quality Frameworks
- Pipeline Monitoring
- Audit Logging
- Performance Optimization
- Production-style Data Engineering practices
🌐 Portfolio:
Gunasekaran Ravi — Data Engineer
💼 LinkedIn:
Gunasekaran Ravi
📍 Location: Chennai, India