Applying AI & Machine Learning to Retail & Ecommerce

APRIL 16, 2025

Jinal Mehta

JINAL MEHTA

Data Engineer II at Amazon

Jinal Mehta is a Data Engineer with over 8 years of diverse experience spanning India, Canada, and the United States. Currently based in Seattle, she works with Amazon’s AIR team, where her expertise in data and passion for problem-solving drive her success. Known for her analytical precision and determination, Jinal thrives on tackling challenges through root cause analysis and delivering impactful solutions. Her international work experience has equipped her with a unique ability to adapt and collaborate across diverse teams and cultures. As an active member of Amazon’s interviewing panel, Jinal contributes to building high-performing teams through technical assessments and candidate evaluations. Outside her corporate role, Jinal is deeply committed to giving back to the tech community. She provides career guidance, interview preparation coaching, and consultation to aspiring data professionals, sharing valuable insights on growth strategies, industry best practices, and practical tips for career success. In her personal time, Jinal enjoys traveling to new destinations, expressing creativity through painting, and staying active by playing badminton. She also relishes quality time with her family and keeps her analytical skills sharp by solving Sudoku puzzles.

Watch live: April 16

Designing Scalable Data Solutions: A Supply Chain Architecture Case Study

I architected a scalable data integration solution that transformed our supply chain analytics, enabling ML-powered predictions from multi-vendor data streams. Drawing from hands-on implementation experience, I’ll share critical insights on designing robust data pipelines for enterprise-scale operations – from handling complex edge cases to ensuring data quality at scale. Join me to discover practical strategies for building resilient data architectures that can drive significant revenue impact through enhanced logistics and supply chain operations.