Hariom Singh

About Hariom Singh

With over 15 years of experience in software engineering, I specialize in building data-intensive and AI-driven platforms at scale. Currently, I serve as a Principal Engineer at Amazon Music, where I lead 9 teams across four critical verticals — Data Platform, Data Quality, Privacy & Compliance, and Tooling & Scaling.Beyond my direct teams, I work at the Amazon Music organizational level (800+ engineers), consulting on data architecture, influencing technical strategy, and shaping long-term data and AI solutions across the company.My work powers systems that process more than 20B+ events daily — starting with SDKs embedded in mobile clients, through a cell-based real-time ingestion architecture, and across pipelines that deliver data in real-time and batch form to 100+ customer teams. These pipelines are built with quality, compliance, and governance by design — from event model validation and real-time DQ checks to GDPR, DMA, COPPA, SOX, and OD3 compliance solutions across S3 and DynamoDB at scale.In addition to distributed data systems, I drive AI-first innovation within engineering- AI-powered large-scale code migration frameworks, accelerating modernization- GenAI based Chatbot- For Generating Analytics Insights, Dataset Discovery, etc- AI-based test case moderation systems for mobile client functional testing.I thrive on solving complex engineering challenges, scaling platforms globally, and building systems that balance technical depth, organizational impact, and future-facing innovation. Alongside delivery, I contribute to thought leadership through technical blogs and mentorship, helping engineers and leaders adopt data and AI solutions effectively.

Experience

1. Principal Software Engineer

   Amazon Music

   Sep 2024 — Present · US

   Transitioned into the Principal Software Engineer role, overseeing data and software initiatives across Amazon Music.* Led development of the Music client SDK for client event ingestion.* Owned and drove GenAI initiatives across Amazon Music.* Built scalable solutions to improve data quality and reliability across Music.* Driving data architecture best practices across Amazon Music.

Education

• National Institute of Technology Agartala

  Bachelor's degree

  2007 — 2011

Skills

• Pl/Sql
• Performance Tuning
• Hive
• Sql
• Amazon Web Services (Aws)
• Hadoop
• Oracle
• Requirements Analysis
• Numpy
• Big Data
• Sqoop
• Plsql
• Python
• Unix