Improved delivery-window accuracy and compliance reliability across 97% of the inbound network by integrating carrier transit-time data and shipment-level capacity validation into the existing computation framework

Enabled a multi-million-dollar shift from fixed rates to dynamic, science-driven pricing for seller shipping costs by developing a new AWS-Lambda-based pricing service and refactoring backend systems to support real-time markup-rate decisions; designed the BI export component processing 20M+ weekly markup records

Unblocked a critical dependency for the launch of an international retail domain (Amazon.ie) by delivering infrastructure mapping and commercial-invoice generation workflows, supporting a $1MM/day revenue launch

Reduced onboarding time for new transportation-compliance use cases from multiple weeks to <2 days by implementing an automated workflow orchestrator and centralized configuration store for templates, replacing a legacy manual process

Drove operational excellence through on-call participation, contributing to CloudAuth migration, mature host cutovers, and migration to modern load-balancer infrastructure, improving authentication resilience and service stability

Led Agile team ceremonies (daily stand-ups, sprint planning, retrospectives, and demos) and managed sprint workflows and team backlog in Asana/Jira to maintain clear priorities, surface blockers early, and improve team delivery cadence

Mentored two junior engineers on communication, prioritization, and time management, and supported new engineers in rapidly ramping up to full development productivity through guided onboarding and hands-on coaching

Reduced data-export time by 67%+ and removed ~8 hours of manual work per transportation change type by redesigning the pipeline into a scalable serverless system (Lambda, Step Functions, Glue, S3), enabling sub-hour onboarding for new change types and safeguarding consistent downstream data through batching, partitioning, and standardized flattening

Data Pipeline: Lessened 30% validation failures by modifying data pipelines for network change validation via SQL

Database Maintenance: Improved query performance by 55% by applying table partitioning in the PostgreSQL database

Backend Development: Enriched UX on the product’s frontend by adding new attributes in data models via Java and SQL

Data Export: Enabled external usage for topology data by automating ETL from internal database to AWS data lake

Technical Procedure Design: Achieved 91% optimizing efficiency by developing an SOP (Standard Operating

A/B Testing: Analyzed AB test results for trending searches to measure the impact of the query filtering and sorting rules

Project Management: Optimized click-through rate by an average of 40 percentage points by leading a team of 3

Data Pipeline: Built data pipeline to automate ETL of search raw data from database to AI cloud via Python and SQL

Strategic Report: Improved algorithm strategies by analyzing search conversions weekly data on problematic indexes

Time-series Analysis: Reduced 20% overstock by conducting a time-series prediction model on print runs

Marketing Analysis: Identified 2 product lines’ major success factors of target markets by applying classification models

Weekly Report: Revised the template of daily/weekly data reports and automated the data preparation process via SQL