Aryan Kadam

I’m an AWS Data Engineer with 2 years of experience developing and deploying cloud-native ETL pipelines, batch processing workflows, and data warehousing solutions. I deliver end-to-end pipeline work from development through deployment, monitoring, and incident resolution in Agile environments.

In my role, I build AWS Glue ETL jobs using PySpark, Python, and SQL to ingest multi-source e-commerce datasets into S3 and transform them through Bronze-Silver-Gold data lake layers. I implement schema validation, deduplication, and business-rule-driven transformations to maintain data quality, and I write outputs in Parquet with partition-based storage to improve Athena query performance and reduce scan costs.

I also automate orchestration and operations across the stack: Glue job bookmarks for incremental ingestion, Glue Data Catalog and crawlers for metadata-driven processing, Lambda with S3 event triggers, and EventBridge scheduling. I monitor pipelines with CloudWatch dashboards, log analysis for root-cause fixes, and configure IAM roles and S3 bucket policies to enforce least-privilege access across Glue, Lambda, and Redshift workloads.