Manali Verma

About Manali Verma

I am a Senior Data Engineer with over a decade of experience designing and scaling real-time data platforms, distributed systems, and AI-driven analytics solutions in high-volume environments.At Amazon, I architect and own large-scale cloud-native data systems that process massive volumes of customer behavior data including search, click, and purchase events. My work focuses on building reliable, low-latency pipelines using Spark, Kafka, and AWS services to enable real-time insights, experimentation, and revenue-critical decision-making.I specialize in:• Real-time streaming and distributed data systems• Scalable ETL and ELT data pipelines• Lakehouse and data warehouse architecture• Data quality and governance frameworks• GenAI and LLM integration into analytics workflows• Performance tuning and large-scale optimizationI have led cross-functional initiatives across Science, Product, and Operations teams, delivering platforms that reduce latency, improve data accuracy, and support multi-million-dollar business impact.Beyond building pipelines, I focus on designing systems that are resilient, scalable, observable, and production-ready. I care deeply about data correctness, performance predictability, and enabling teams to move faster with trusted data.Currently open to opportunities where I can contribute to building high-scale data platforms, real-time intelligence systems, or AI-driven infrastructure in technology, fintech, or data-focused organizations.

Experience

1. Senior Data Engineer

   Amazon

   Jun 2024 — Present · Bengaluru, IN

   Leading a team for end to end infrastructure for Customer behaviour and Amazon Retail Business services of Petabytes of data size (10 Billion), enabling product teams to analyze adoption, usage, and revenue trends, as well as assess the impact of new feature launches. Leveraged SQL and PySpark to create scalable data models and pipelines that efficiently processed large datasets.• Built and maintain data pipeline on 500 Millions per day to 14 Billion (300 TB) at the time of sales for Amazon Retail & Business in <10 min using AWS. Enabled and provided data to the Sciences team through AWS DDB and S3 to produce low latency analytics and insights for failure detection, time-critical service reactions, root cause analysis, business decisions and strategise the product selling and growth through Quicksight and Tableau dashboard.• Designed Data Quality detection and analysis API-based capability to identify the data quality issues using Glue catalog scripts, which aims to improve Data Quality and increase the population & accuracy of key fields. Provided generic pipeline to 100+ Amazon internal teams and 10M+ of data transforming jobs are executed every day.• Designed and developed KPIs for monitoring to help the sales in Subscribe & Save make data-driven decisions

Education

• Kendriya Vidyalaya

  Senior Secondary Examination, Physics, Chemistry, Biology, Mathematics

  1997 — 2011

• INDIRA GANDHI DELHI TECHNICAL UNIVERSITY FOR WOMEN

  Bachelor of Technology (B.Tech.), Computer Science Engineering

  2011 — 2015

• Indian Institute of Information Technology Kottayam

  Master of Technology - MTech, Artificial Intelligence and Data Science

  2020 — 2023

Skills

• Pl/Sql
• Database Design
• Program Development
• Operating Systems
• Extract, Transform, Load (Etl)
• Html
• Seismology
• Shell Scripting
• Game Design
• Unix
• Characterization
• Oracle Database
• Oratory
• Data Mining
• Informatica
• Mobile Game Development
• C++
• Mysql
• Data Analysis
• Database Administration
• Data Center Design
• Software Engineering
• Web Logic
• Hadoop
• C++ Language
• Matlab
• Javascript
• Computer Language
• C
• Programming
• Software Design
• Strategic Planning
• Information Technology
• Java
• Coding Languages
• Sql
• Linux
• Apache
• Petroleum Engineering
• Reservoir Management