Python Engineer

DIVYANG PARMAR

Clifton, NJ 862-***-**** *******.**********@*****.*** linkedin.com/in/divyangparmar TECHNICAL SKILLS

● Languages: Python, SQL, Shell Scripting, HTML, CSS.

● Methodology: Agile, Waterfall.

● Testing Methodologies: Unit Testing, Integration Testing.

● Databases: SQL Server, AWS Aurora, AWS RDS, AWS DynamoDB, Oracle 11g, MySQL.

● API: Twitter, GitHub, Slack, Web Endpoint.

PROFESSIONAL EXPERIENCE

Bank of America Python Developer NJ Feb 2019 - Present

● Designed & architected OTC derivative related ETL system using Python, Bob Job & 3rd party APIs

● Optimized the batch job loaders of a columnar database using Python packages resulting in 50% improved execution

● Improved the execution of the recon scripts counting trades & deals between new & old ETL systems to aid the testing process

● Created the POC for the new ETL system by reconciling the IMs with the existing system thereby initializing the development

● Technologies and framework used - Python 3.6, SQL, Pandas, JIRA, Confluence(documentation), API Integration Verizon Python Developer NJ Oct 2018 - Nov 2018

● Developed a single instance running Korn shell script to call the ETL pipeline ensuring only one instance is initiated at a time.

● Created ETL pipeline to automate the reading of data files from 7 different sources each having 28 network depots concurrently

& store it in AWS S3 buckets.

● Designed & developed AWS Lambda triggers to transform the data from AWS S3 buckets to AWS Aurora

● Technologies and framework used - Python 3.6, Shell scripting, Vim, Unix, AWS S3, AWS EC2, AWS Aurora, AWS Lambda, Git.

Lumeris Healthcare Inc. Python Developer MO May 2018 - Oct 2018

● Optimized the workflow scripts involving complex calculations using python & SQL which in turn reduced the turnaround time.

● Automated the user enrollment process of the new system thereby reducing the manual hours.

● Technologies and framework used - Python 3.6, Shell scripting, Kanban, Katalon, JSON, Pandas Nomura Holding America Inc. Data Engineer Intern NY Jun 2017 - Dec 2017

● Developed a python script to accurately identify & reconcile the usage of trader phones thereby saving the company $500K

● Saved 2 hours of daily data munging task using python scripts that combine data from multiple feeds & perform dimensionality reduction Built a python tool to automate the feeds from 3 different systems to audit the new traders that are to be recorded.

● Technologies and framework used - Python 3.6, Pandas, NumPy, SQL, Unix, REST, JSON, Shell Scripting, Git. 3i Infotech Ltd. Full-Stack Engineer Mumbai, India Jul 2014 - Jul 2016

● Re-engineered the backend system involving account setup, creation & modification using PL/SQL resulting in 45 mins reduced run time.

● Improved the speed of data load by 36% by optimizing backend scripts that load data from different pipelines into ETL systems. Technologies and framework used - Core Java, JSP, Python 3, EJB, HTML, CSS, AJAX, and Oracle. EDUCATION

Master of Information Technology, Rutgers University, Newark, NJ Aug 2016 - Dec 2017 Bachelor of Computer Science, Narsee Monjee Institute of Management Studies, Mumbai, India Aug 2008 - Jul 2012 PROJECT WORK

Crime Prediction in Chicago City ETL Engineer Mar 2017 - May 2017 Building an ETL pipeline the crime in Chicago City

● Built pipeline to extract the dataset from Kaggle using Kaggle API by scripting in Python.

● Transformed by removing the unwanted null values & duplicate data, converting into a standard format to load it into SQL Server.

● Used Naïve Bayes Algorithm to predict the crime in the Chicago city by crime type and visualize the data to identify seasonal trends in the crime and used multivariate regression to understand the factors. Sentiment Analysis of Top Trending Topics in Twitter Python Developer Mar 2017 - May 2017 Built a data pipeline to do sentiment analysis on twitter data

● Built a data pipeline to ingest the tweets stream from twitter API, transforming and storing in SQL Server

● Analyzed the top trending topics from the hashtags and performed sentiment analysis to gain insights using Python.

● Used NumPy, Pandas, and NLTK packages for the analysis.

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