I am a graduate student from Northeastern University with Master’s in Information Systems, looking for full-time opportunity starting May 2020.
I am a professional with 4 years of experience of Data and Test Analyst at HSBC software development and 6 months of co-op experience in Data engineering at Granite Telecommunications.
My work as a Data Analyst and Test Analyst at HSBC made me understand, how data can drive the organization towards success or failure. I want to be a part of this data-oriented process to help any organization with my skills of Analyst and Engineer. This is where my interest towards data engineering evolved and I wanted to work in this field and learn more and more about it every single day.
I like to explore and learn different technologies to solve different problems by not sticking to what I already know but ready and curious about new technologies. As it is said “Modern problems require modern Solution”, so why not go for modern solutions.
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Experience
Granite Telecommunications Aug 2019-Dec 2019
Data Engineer Co-op
• Migrated data from SQL Server & Oracle to Hadoop cluster Impala using Sqoop increasing execution speed by 35%
• Owned an automation task for the Sqoop Statement creation process using python reducing manual efforts by 80%
• Wrote stored procedures on impala which increased speed of execution of that process by 40% • Integrated Hive with Power BI to create Interactive dashboards using Cloudera ODBC connection on Hue Platform • Implemented ETL (SSIS) to create jobs for extracting, cleaning, transforming and loading data into data warehouse and implementation of web service task
HSBC Software development
Data Analyst Mar 2017-Jul 2018
• Performed database development, testing, business analysis, production support being a part of a cross-functional POD
• Probed business impacting production issues using Unix and SQL and worked on implementation of multiple release • Developed sub-queries, complex Stored Procedures, Triggers and Views on Oracle and MySQL
• Wrote a python script to automate the generation of matching counterparty SWIFT Trade data with the Host data
• Analyzed and optimized existing SQL queries for performance improvements increasing code efficiency by 40%
Test Analyst Jul 2014-Mar 2017
• Oversaw a team of 5 on a tier 0 application and worked on performance, system integration, user acceptance, regression testing and managing complete testing cycle in Agile Scrum
• Co-ordinated with business stakeholders to understand business requirement and convert into functional requirement for Treasury confirmation matching system dealing with FX, MM, PM and Options
• Led a team on automation of regression pack conserving around 80% of manual testing task leveraging TOSCA tool
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Projects
Data Warehousing and Business Intelligence for Retail Sales (Talend, Data Modeling, Tableau, Power BI) Sep 2019-Dec 2019
• Designed a master job to populate a retail data warehouse on Talend, loading 40 million rows in 20 minutes
• Implemented Source to Target Mappings, Data Profiling, ETL flows, Slowly Changing Dimensions, Reject Codes, Currency Conversion and Performance Tuning on data sourced from SORs (MySQL, SQL Server, Postgres, Oracle and Excel)
• Generated interactive KPI dashboards to convey stories of retail sales using Tableau and Power BI
Crimes in Boston Data Analysis and Visualization (Python, CouchDB, Power BI,Postman) Jul 2019-Aug 2019
• Devised Data pipeline using python to insert data from excel source into CouchDB in JSON format, reducing the manual insertion efforts by 60%
• Built interactive visualizations on Power BI by establishing connectivity through API using Postman with CouchDB
Weather App (Python, Tkinter) Mar 2019-Jun 2019
• Created an application which fetches weather data based on location entered by user
• Integrated a weather API into Application and built user interface with tkinter library of python
Bank Marketing Analysis Using Python (NumPy, Pandas, Matplotlib, Seaborn, S3, Sagemaker) Jan 2019-Feb 2019 • Performed data cleaning and data pre-processing of raw data and applied logistic Regression and Classification techniques to predict whether a customer would subscribe to a term deposit
• Established data processing using NumPy and Pandas, Visualized results using matplotlib and seaborn libraries