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Nagesh Panditi

@nageshpanditi

Data Engineer at Deloitte USI building reliable GCP pipelines, including BigQuery workflows that cut query execution time by 35%.

India

Message

At Deloitte USI, I build and maintain data workflows for financial services and retail clients. I developed BigQuery transformations that reduced query execution time by 35%, and Python and PySpark workflows that reduced processing time by 40%.

Previously, at Syntel Pvt Ltd, I ingested daily data into Hive, implemented real-time ingestion with Apache Kafka, and automated Airflow workflows. I also built a real-time processing project with Apache Beam and Google Cloud Dataflow, and a BigQuery data warehouse using Medallion Architecture.

Experience

Work history, roles, and key accomplishments

Current

Data Engineer

Current

Deloitte USI

Feb 2025 - Present (1 year 9 months)

Architected and maintained 25+ daily batch ETL workflows using Google Cloud Composer, improving pipeline success rates above 99%. Optimized BigQuery transformations and PySpark jobs, reducing query execution time by 35% and processing time by 40%.

Google Cloud Composer Airflow BigQuery PySpark Dataproc Google Data Fusion Pub Sub Python SQL Jira Bitbucket Bamboo CI CD

Data Engineer

Syntel Pvt Ltd

Oct 2021 - Nov 2024 (3 years 1 month)

Ingested over 15 GB of daily data into Hive using Python and SQL, and implemented real-time ingestion with Apache Kafka. Automated workflows with Airflow, reducing manual intervention by 30%.

Python SQL Hive Kafka PySpark BigQuery Airflow Google Cloud Storage