Harish Aravindh Mahendran

I am a Data Engineer with five years of experience building and optimizing cloud-based data platforms and ETL pipelines for telecom and banking domains. I focus on designing scalable PySpark and Python data workflows on Databricks and AWS to process millions of records reliably.

I have led SAS-to-Python migrations, implemented production-grade ETL using Databricks and AWS Glue, and created backward-compatible Redshift views to ensure seamless legacy migrations. My work emphasizes performance optimization through partitioning, caching, efficient formats, and memory-efficient Python techniques.

I build API-driven ingestion, orchestration with Lambda and Airflow, automated monitoring, and GenAI proofs-of-concept using LLM frameworks for internal automation and experimentation. I also develop time-series forecasting and anomaly-detection models to deliver analytical insights.

I collaborate closely with stakeholders to translate business requirements into production-ready solutions, and I have been recognized for high-impact client delivery and performance in previous roles.