Ajaikumar Anil

I’m a Data Engineer with 2.9 years of experience specializing in building scalable ETL pipelines and serverless data solutions. I focus on production-grade reliability, turning raw data into analytics-ready datasets that teams can trust.

At Muthoot Fincorp Ltd, I engineered a high-throughput Customer360 pipeline processing 15 million+ records using AWS Lambda and API Gateway to unify partner data and reduce onboarding latency. I also built end-to-end ETL workflows on a co-lending platform with AWS Glue and PySpark—covering ingestion, validation, transformation, and document processing for consistent data quality.

I’ve led data migration efforts as well, transferring data from AWS S3 to on-premise MS SQL Server using AWS Glue and Python to ensure downstream analytics and reporting stay continuously available. I automated daily MIS and operational reports using Python (Pandas) and SQL, eliminating manual reporting effort and improving metric accuracy while cutting manual processing time by 3–4 hours daily.

Beyond my core role, I strengthen my craft through projects like a Reddit ETL pipeline using Apache Airflow (Docker), AWS S3, AWS Glue, and Amazon Redshift, where I orchestrate ingestion, transformation to Parquet, and scheduled execution. I’m also building hands-on ETL validation experience with a Loan Applications pipeline in PySpark and PostgreSQL, and I’m currently expanding into Azure Data ecosystems through “Azure Data Engineering (currently upskilling)”.