RAHIL NALIN SHAH
San Francisco Bay Area ****.***@*****.***.*** +1-978-***-**** LinkedIn: rahilshah10 GitHub: rahilshah10 EDUCATION
Northeastern University, San Jose, CA Sep 2017 – Dec 2019 Master of Science in Information Systems, 3.56 GPA K.J. Somaiya College of Engineering, Mumbai, India Aug 2013 – May 2017 Bachelor of Engineering in Electronics Engineering TECHNICAL SKILLS
Languages: Python SQL NoSQL Java HTML CSS JS Angular Technology: Apache Spark TensorFlow Hive Hortonworks Toad Visual Studio AWS Lambda Databases: MySQL PostgreSQL MongoDB Athena Oracle SQL SQL Server Database Integration: Talend SSAS SSIS SSRS Alteryx AWS Glue BI and Analytics: Tableau Qlik Sense Microsoft Power BI AWS QuickSight WORK EXPERIENCE
Granite Telecommunications, Quincy, MA
Data Analyst Intern Aug 2018 – Dec 2018
Big Data and Business Intelligence (Hadoop, Hive, SSIS)
● Developed an ETL pipeline to extract ~130 million rows of data from SQL Server & Oracle and loaded in Cassandra Hadoop cluster; increasing speed by 62%
● Created PowerBI dashboards pertaining to customers, tickets, and inventory to identify churn and aid retention Database Developer (SQL Server, OracleDB)
● Implemented protocols to log DML changes, enhance security and resilience to SQL injection by creating around ~3000 stored procedures and necessary triggers
● Improved transaction speeds by performing query tuning and migrating stored procedures from SQL Server to Oracle
● Set up better database administration protocols to reduce privilege abuse and weak audits PROJECTS
Serverless Data Analysis (AWS Lambda, AWS Glue, AWS Athena, AWS QuickSight) Oct 2019
● Developed a pipeline to daily scrape, preprocess and append ~1600 rental data from Craigslist using Python on AWS Lambda
● Used AWS Glue to transform the data from JSON to Parquet format in order to achieve 99.7% cost savings
● Used Amazon Athena for querying the underlying data in a serverless setting for exploratory analysis
● Created a dashboard in QuickSight, which updates periodically, in order to see trends and gain insights Data Warehouse (Talend, SSIS, SSAS, PowerBI, Tableau, Qlik Sense) May 2018 – Aug 2018
● Developed a data warehouse, pipelining data from diverse sources using Talend Data Integration and SSIS
● Created and optimized processes in the data warehouse to import, retrieve and analyze data in the Retail System
● Implemented error handling, load statistics, slowly changing dimensions, currency conversion, and performance tuning
● Built custom dashboards to analyze sales and customer segmentation using Tableau, Qlik Sense, and PowerBI Ride Sharing Optimization (Python, Apache Spark, TensorFlow, Facebook Prophet) Jan 2018 – Apr 2018
● Streamlined choice–making process between Uber and Lyft to create an efficient data model for both drivers and passengers by showing real time and future price estimates
● Compiled a python script to get latest data from Uber, Lyft, Yelp, Open Weather APIs and automated it on Amazon EC2 creating about 86,400 rows of data over 2 months
● Forecasted ride sharing price estimates with TensorFlow utilizing RNN with a Mean Squared error of 0.7119
● Developed an additive model for time series data utilizing Facebook Prophet package to forecast ride sharing price estimates one day ahead and show an overall trend, weekly trend, daily and time of day trend Database Design for App Store (SQL Server, SSAS, SSIS, SSRS, Toad) Jan 2018 – Apr 2018
● Designed complete back end database system to support an App Store operating Toad with 20 entities in 3rd Normal Form
● Deployed and evaluated the complete design on SQL Server and populated sample data from a flat file using SSIS with data from 500 sample applications
● Managed documentation regarding the business requirements, relationships and entities to make this database design EXTRACURRICULARS
● Received accolades for creating the best visualization at Code for San Jose on their National Day of Civic Hacking event
● Mentored and guided hearing-impaired students in mathematics improving overall class performance by 30% & learned basic Sign language to communicate with hearing-impaired students