Shruti

Work Experience

Production data engineering work across AWS, warehouses, ETL, and large-scale migrations, with measurable performance and reliability improvements.

Full‑time

Data Engineer — Quantiphi

Mumbai, India • July 2023 – Present

AWS PySpark Redshift Snowflake Python SQL LLM

Impact

  • Migrated 78+ Statistical Analysis System (SAS) processes to PySpark on AWS Glue, reducing execution time by ~30% while preserving functional parity.
  • Worked across three client groups; led Business Acceptance Testing (BAT) and End‑User Testing (EUT), partnering with business users to validate outputs against legacy SAS while maintaining compliance and data integrity.
  • Engineered a 50+ TB financial data warehouse in AWS Redshift; designed ETL pipelines and optimized SQL to support production revenue planning/reporting.
  • Automated ingestion + file transfer pipelines with Python, reducing manual upload/validation work by 70%.
  • Built an automated Redshift vacuum trigger using AWS Step Functions and ECS, reducing downtime by 40%.
  • Performed EDA on 10+ TB financial datasets and improved data quality by 30% through targeted fixes and validation checks.
  • Developed an LLM utility for an AI-powered agent, reducing manual efforts for project documentation by 50%.
  • Designed and optimized SQL workflows in Snowflake to improve query performance for analytics and reporting workloads.
  • Received recognition in a client newsletter for independently driving test cycles and delivery coordination.
Internship

Data Engineer Intern — Quantiphi

Mumbai, India • Jan 2023 – Jul 2023

AWS S3 Pandas REST APIs Tableau SQL

Impact

  • Built ETL pipelines for financial datasets using AWS Athena, S3, and Pandas to automate reporting for 50k+ records/day.
  • Designed interactive Tableau dashboards that reduced reporting time by 50% and enabled senior leaders to monitor KPIs in near real time.
  • Integrated REST APIs into ETL workflows to pull external data into S3 with automated refresh cycles, improving report accuracy by 25%.
  • Performed data cleaning and transformations to improve data quality by 30% for downstream reporting.