Mukund Kulkarni Engineering Scalable Pipelines & Intelligent Systems.

Manager

• • Designed a modular data pipeline in GCP Dataflow that processed both NRT and RT data feeds leveraging Bigquery, PubSub and Cloud Bigtable.
• • Procesed over 10k+ new NRT records and 100 transactions/s of RT records daily to derive and update more than 100+ attributes and made them available for consumption for credit decisioning.

Senior Analyst

• • Developed data pipelines using GCP, dbt, and Airflow designed for high-velocity consumption (200 transactions/ms), enabling real-time analytics and decision support for Fraud and Credit services.
• • Implemented usecases for Credit Limit Increase, Mortgage Process Optimization and World Class Onboarding (ETB and OD).
• • Developed and optimized end-to-end ETL pipelines using BigQuery, implementing partitioning and clustering strategies to improve query performance and reduce storage costs.
• • Worked and improved upon a custom dbt operator in Airflow to orchestrate dbt model execution, providing a robust and scalable solution for data transformation pipelines.
• • Designed and implemented a Looker dashboard to provide real-time monitoring, in-depth analysis, and automated alerts for the health and performance of multiple data pipelines.

ETL Developer

Engineered distributed ETL pipelines for a tier-1 global credit processing company. Authored and optimized robust Apache Spark scripts leveraging Google Cloud Platform for transforming, processing, and analyzing massive consumer financial datasets with strict SLA adherence.

SAS Programmer

Managed and analyzed large-scale consumer transactional data utilizing Statistical Analysis System (SAS). Architected automated custom reporting workflows and data models aligned with core business requirements.

Migration Analyst

Led cloud migration initiatives for enterprise data applications to Google Cloud Platform. Performed end-to-end data validation, architectural analysis, and redesigned legacy batch workflows into cloud-native architectures.

Machine Learning Intern

Conducted cutting-edge research on the Unmixing of Hyperspectral Satellite Data using Convolutional Neural Networks (CNNs). Built deep learning architectures to extract endmembers and predict fractional abundances from complex multi-band satellite sensor data.

Web Development Intern

Architected and developed the responsive primary landing page and user interface for the company. Implemented dynamic views and modular UI components leveraging Django and modern frontend styling.