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Gaurav Ghosh

@gauravghosh

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Data Engineer at Accenture who cut Spark pipeline runtime by 99.9% on billion-record financial datasets.

India

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At Accenture, I architected an automated Spark and Hive pipeline that cut processing time for fee data from two weeks to 15 minutes. I also developed fee-computation logic that was approved by senior directors for its revenue impact.

I build and optimise data pipelines with Spark, Hive, Python, and AWS, and have applied LLM-powered automation to engineering workflows. At Accenture, I currently mentor and lead three junior engineers; at LTIMindtree, I built data quality frameworks that reduced data errors by 60%.

Experience

Work history, roles, and key accomplishments

Current

Specialist Data Engineer

Current

Accenture

Aug 2024 - Present (2 years 2 months)

Architected end-to-end automated Spark and Hive data mining pipelines processing 500M-1B records, reducing runtime by 99.9%. Owned novel fee-computation logic with multi-million dollar revenue impact and led a team of 3 engineers.

Apache Spark Hive Python AWS Glue S3 IAM Databricks CDP LLM Generative AI SQL Java Partitioning ETL CI CD

Senior Data Engineer

LTIMindtree

Jul 2021 - Aug 2024 (3 years 1 month)

Designed and maintained ETL pipelines on a star-schema data model across 700M+ records. Built automated data quality frameworks reducing data errors by 60% and owned CI/CD orchestration via Autosys and Jenkins.