Data Engineer

SENAKSHI KRISHNA MURTHY

Maryland (Open to relocate) ***********@*****.*** Linkedin Github

EDUCATION

Master of Professional studies in Data Science August 2024 - May 2026 University of Maryland Baltimore County - Baltimore Bachelor of Engineering August 2017 - August 2021

Adichunachanagiri Institute of Technology - India

TECHNICAL SKILLS AND CERTIFICATION

Languages Python, SQL, Scala, Pyspark, Shell Scripting, VBScript, Hive, SparkSQL Tools Git, Jira, Azure Devops, Jams, Dbeaver, VS code, Microsoft Azure, Scikit-learn Database MySql, HDFS, MariaDB, MongoDB

Methodologies & Concepts Apache Spark Linux, Unix, Apache Hadoop, ETL, Pyspark, Machine Learning Certification Microsoft Certified: Azure Data Engineer Associate, Foundation of Cybersecurity EXPERIENCE

Data Engineer November 2021 – July 2024

Infosys Limited -Mysuru, India

• Developed and implemented robust data delivery systems for a financial services client focused on mortgage platforms, enhancing real-time collaboration by 35% between back-office and mid-office teams.

• Spearheaded data management initiatives, leading the development and documentation of efficient data loading processes using PySpark that ensured high-quality results through rigorous testing protocols with MySQL and MariaDB across 50+ datasets.

• Oversaw business rules and transformations in Informatica BDM, optimized job schedules and workflows, and via JAMS it was monitored and alerted which impatcted 40% of the final result.

• JIRA was tool to manage projects and report team progress on individual and group assignments which had 95% efficiency.

• Quality Assurance was proven a solid track record in acceptance testing and data validation, guaranteeing clients receive reliable data for 20+ years. I also provided training to new hires on standard practices for development and testing.

• Testing and Implementation of new data sources around 10+ were successfully incorporated into current work- flows by testing the PySpark framework for data loading and creating VBScript for data sorting.

• Facilitated the integration of a unified database system that improved data flow management, resulting in a 60% improvement in response times to client inquiries and increased satisfaction scores by 15 percentage.

• Enhanced interdepartmental collaboration by streamlining data workflows for 15+ clients, resulting in improved information accuracy and a decrease in project turnaround time by nearly 30% through effective communication strategies.

PROJECTS

Meta data Analysis:

• In this case, the data set consists of your own browser history, and Python & Pandas to filter out the domain from all the data and with matplotlib for visualization which allows us to infer the user’s personality.

• Consequently, this technique is used in 90% of messaging services with end-to-end encryption, preventing the company from ever seeing the exact message.

Baltimore crime rate analysis:

• The analysis made examined violent crime trends (homicides, shootings, and aggravated assaults) in Baltimore from 2017 to 2024.

• Using data from police records, violent crimes were aggregated by neighborhood and year, filtered for anomalies, and analyzed to compute absolute and percentage changes using Python, Numpy, and Pandas. Visualizations made using the code which included bar charts and showcased significant findings of the crime rate. Rainfall forecasting:

• Analyzed historical rainfall data to develop predictions, visualized trends through graphs, and presented insights using Python with any accuracy of 70%.

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