Nisha Chandwani
Data AnalystSenior Software Engineer at Amazon
Amazon
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Senior Software Engineer at Amazon
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Indiana University Bloomington
Master of Science (MS), Computational Science
January 1, 2016 – January 1, 2017
Government College of Engineering Amravati
Bachelor of Technology (B.Tech.), Information Technology
January 1, 2006 – January 1, 2010
Amazon
Senior Software Development Engineer
April 1, 2026 – Present
Seattle, Washington, United States · On-site
Amazon
Software Development Engineer II
October 1, 2020 – March 1, 2026
Seattle, Washington, United States · On-site
Amazon
Software Development Engineer I
November 1, 2018 – September 1, 2020
Seattle, Washington, United States · On-site
Autodesk
Conversation AI Engineer
March 1, 2018 – November 1, 2018
San Francisco Bay Area
Indiana University Bloomington
Associate Instructor
August 1, 2017 – December 1, 2017
Greater Bloomington, Illinois Area
Amazon
Intern (Data Science/Analytics)
May 1, 2017 – August 1, 2017
Greater Seattle Area
Deloitte Consulting
Consultant (Data Warehousing/Data Engineering/BI/ETL)
December 1, 2013 – July 1, 2016
Mumbai Metropolitan Region
Charter Global
Senior Technical Developer (Data Warehousing/Data Engineering/BI/ETL)
September 1, 2012 – November 1, 2013
Pune/Pimpri-Chinchwad Area
Tata Consultancy Services
Systems Engineer (Data Warehousing/Data Engineering/BI/ETL)
June 1, 2010 – August 1, 2012
Mumbai Metropolitan Region
Cloud File System
January 1, 2018 – Present
Developed a multithreaded, stateless cloud file system for storage, access and retrieval of large files. Used Java for development and VirtualBox swarm for testing.
Information Retrieval System
November 1, 2017 – Present
Worked on an academic project to generate the index for a corpus using the Lucene API in Java, while using the generated index to extract information about the corpus. Used KeywordAnalyzer, SimpleAnalyzer, StopAnalyzer and StandardAnalyzer for indexing.
Image Classifier
December 1, 2016 – Present
The task was to identify the correct orientation of a given test image. Implemented k nearest neighbors algorithm to predict the orientation of a given image using the training dataset consisting of images and their correct orientation.
House Price Prediction
November 1, 2016 – Present
Participated in the Kaggle competition to predict sale prices of residential homes in Ames, Iowa. The provided dataset included 79 explanatory variables describing various aspect of the residential homes. Performed data cleaning, exploratory data analysis and used ridge and lasso regression techniques for predicting the sale prices.
Document Classifier
November 1, 2016 – Present
Built a document classifier for filtering spam emails with the help of a large training dataset consisting of both spam and non-spam emails. Built two versions of the document classifier - one using Naive Bayes and the other using a Decision Tree. Implemented the decision tree from scratch in Python.
Natural Language Processor
October 1, 2016 – Present
Implemented part-of-speech tagging with the goal of associating every word in a sentence with its part of speech. Modelled the part-of-speech problem into three different Bayesian Networks. Implemented these networks using three different techniques - Naive Bayes, Viterbi algorithm and Variable elimination.
Tetris Game Player with AI Component
September 1, 2016 – Present
The goal was to implement a computer player for Tetris that scores as high as possible by selecting the best possible position for the falling piece.
Data Integration for Healthcare Client
August 1, 2015 – July 1, 2016
The client is one of the largest multinational medical devices, pharmaceutical and consumer packaged goods manufacturer in the United States. • Analyzed the functional design specification and designed the Enterprise Data Warehouse data flow for one of the largest multinational medical devices, pharmaceutical and consumer packaged goods manufacturer in the United States • Performed ETL (Extract, Transform and Load) using Informatica and data transformation using Oracle PL/SQL to obtain datasets for analysis of the sales details of the products and the associated complaints • Visualized the data for signal detection for product safety using Tableau
Data Integration and Warehouse Building
December 1, 2013 – July 1, 2015
The client is a U.S. Cellular Services Provider. • Worked on the enhancements to the existing data warehouse and its quality assurance • Developed Informatica mappings and associated workflows for data integration • Performed integration testing and regression testing to validate the system • Worked as a module lead and managed a team of more than 10 practitioners based out of multiple locations
Design and build Enterprise data Warehouse
September 1, 2012 – November 1, 2013
The client is one of the largest wireless Telecommunications network in the United States. • Developed a centralized non-volatile data store for enterprise reporting for one of the largest wireless Telecommunications network in the United States. The project aimed to dislodge the two existing data stores and bring up a singular enterprise Customer data warehouse • Performed ETL using Informatica for integrating the call data records for analysis • Developed scripts to load data in Teradata using data loading utilities like TPT (Teradata Parallel Transporter) • Developed scripts in Tivoli for scheduling the data loads in the enterprise warehouse
Sourcing Workbench
June 1, 2010 – August 1, 2012
The Client is a leading name in healthcare domain and provides a range of products and services that include medical imaging and information technologies, medical diagnostics, patient monitoring systems, drug discovery and biopharmaceutical manufacturing technologies. • Developed a centralized data warehouse for the client, a leading healthcare provider in the United States, to enable reporting the purchase details and thus optimize profit • Worked as an ETL developer and extracted data from various sources like SAP, flat files and Oracle • Developed scripts in Redwood Cronacle for scheduling the data loads in the warehouse
Teradata 12 Certified Professional
Teradata
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a diverse project background, ranging from academic machine learning and AI projects to extensive enterprise data warehousing and ETL roles. The transition from data engineering/warehousing to a more data science/analytics focused internship at Amazon, and then to SDE roles, indicates adaptability. However, the recent SDE roles at Amazon (2018-present) are less directly aligned with a pure Data Analyst role, potentially indicating a shift in career focus or a broad skill set that needs to be re-aligned. The target role of 'Data Analyst' aligns well with the earlier career and internship experiences, but less so with the recent SDE roles.
Soft Skills & Operational Fit
The candidate's experience as a module lead at Deloitte Consulting and Charter Global suggests strong leadership and team management skills. The project descriptions indicate an ability to analyze functional specifications and design data flows, pointing to good problem-solving and analytical capabilities. The academic projects showcase initiative and independent learning.