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Gayatri Ballal

@gayatriballal

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Data Engineer building scalable AWS ETL pipelines and lake/warehouse solutions with Spark, PySpark, and Glue.

India

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What I'm looking for

I’m looking for a role where I can build trusted, analytics-ready data pipelines on AWS—own ETL/lake-warehouse design, strengthen data quality and reliability, and use automation, monitoring, and performance tuning to power business reporting.

I’m a Data Engineer focused on building scalable ETL pipelines and data lake/warehouse solutions on AWS. I design and deliver analytics-ready datasets with reliable ingestion, strong data quality, and performance tuning—using Spark/PySpark, Hive, AWS Glue, Athena, Redshift, and EMR.

At Nexus Software System, I implemented Medallion Architecture (Bronze/Silver/Gold) to reduce data inconsistencies by 30–35%, and I automated and monitored end-to-end pipelines with Apache Airflow, CloudWatch, and AWS Glue. I also optimized Spark jobs and Hive queries to cut execution time by 30–40%, and I perform validation and reconciliation between source and target systems to ensure trusted reporting for business insights.

Experience

Work history, roles, and key accomplishments

Current

Data Engineer

Current

Nexus Software System

Aug 2023 - Present (2 years 10 months)

Built scalable ETL/data pipelines with PySpark, SQL, and AWS Glue to ingest data from Amazon RDS (PostgreSQL) into Amazon S3, improving data availability. Implemented Medallion Architecture and optimized Athena/Redshift and Spark/Hive jobs, improving data quality by 30–35% and reducing execution time by 30–40%, while automating and monitoring workflows with Airflow and CloudWatch.