Saravanan Nagaraj

I’m a Cloud Data Engineer with 3.5+ years of experience designing and developing scalable data pipelines across Azure and Snowflake. I focus on building end-to-end data platforms using modern ELT architectures and the Medallion (Bronze–Silver–Gold) framework for reliable analytics.

At HCLTech, I designed and developed batch processing architectures for lottery systems—ingesting data from multiple terminals, POS systems, and enterprise sources. I built scalable PySpark-based ingestion and transformation pipelines to cleanse and process large volumes of data, efficiently loading business-ready datasets into Snowflake Data Warehouse (processing 250+ GB of lottery transaction data).

I orchestrate end-to-end workflows using Apache Airflow and Azure Data Factory (ADF) across on-premises and cloud environments, and I develop reusable PySpark frameworks for data validation, transformation, and error handling. I care about operational excellence, so my work emphasizes automated, cost-efficient pipelines for both batch and incremental processing.

Previously at Claysys Technologies, I delivered multi-cloud ELT pipelines using Snowflake and Azure, including raw, staging, intermediate, and mart layers for high-performance analytics and BI workloads. I implemented dbt snapshots for Slowly Changing Dimension (SCD) Type 2, optimized Snowflake with micro-partitioning and clustering plus query tuning, and built CDC solutions to process incremental changes. I also created data quality frameworks (validation rules, reconciliation, and monitoring) to improve accuracy, consistency, and trustworthiness.