Indumathi 👋

Designed and optimized large-scale data infrastructure supporting analytics workloads for enterprise clients. Led development of complex BigQuery stored procedures and SQL queries that processed millions of records daily, improving query performance and reducing compute costs through strategic optimization and schema design.

Automated end-to-end ETL pipelines using Talend and Automic Scheduler, establishing monitoring frameworks that reduced manual intervention and improved system reliability. Implemented comprehensive data validation and quality checks across production systems, ensuring accuracy and consistency of downstream analytics.

Recognized for contributions to data quality initiatives and delivery excellence in February 2024. Received multiple client appreciation awards in July 2023 and March 2023 for consistent technical execution, reliability, and impact on critical data infrastructure projects.

Built and maintained data ingestion pipelines on Google Cloud Platform, loading enterprise data at scale into BigQuery for analytics and reporting. Developed Python preprocessing scripts to transform diverse source formats into BigQuery-compatible structures, handling edge cases and ensuring data integrity throughout the ingestion process.

Performed SQL development and validation using DBeaver, maintaining comprehensive documentation for data ingestion workflows and transformation logic. Collaborated with cross-functional teams to troubleshoot production issues and implement solutions that improved pipeline stability.

Promoted to Data Engineering Analyst within first year based on technical contributions, ownership, and consistent delivery of high-quality solutions.