Parva Shah
@parvashah
Experienced Software Developer with a passion for data analysis.
What I'm looking for
As a seasoned software engineer and data engineer, I leverage my expertise in improving system efficiency and delivering impactful results. With a strong background in computer science and a Master's degree from the University of Texas at Arlington, I excel in optimizing data processing, automating test execution, and developing scalable RESTful APIs.
My professional experience spans across top-tier companies like Fannie Mae and Amazon, where I have successfully provisioned and managed AWS infrastructure, implemented and optimized ETL pipelines, and automated CI/CD pipelines. I am well-versed in a range of programming languages, including Python, Java, and C++, and have a strong understanding of data analytics, machine learning, and cloud computing.
With a passion for innovation and a drive to deliver results, I am committed to staying at the forefront of industry trends and technologies. I am excited to bring my skills and expertise to a new challenge and contribute to a team that shares my passion for excellence.
Experience
Work history, roles, and key accomplishments
Software Development Engineer
AMAZON
Aug 2021 - Feb 2023 (1 year 6 months)
Enhanced the Dafny compiler and interpreter, reduced automated test execution time by 60% through GraphQL API optimizations, and automated ETL processes with Python.
Network/IoT Development Intern
DARKHORSE
Sep 2020 - Jan 2021 (4 months)
Programmed Nordic Semiconductor devices to record and transmit accelerometer and GPS data, and created AWS Lambda pipelines.
Education
Degrees, certifications, and relevant coursework
University of Texas at Arlington
Master of Science, Computer Science
2019 - 2021
Completed a Master's degree in Computer Science, focusing on advanced topics in software development and data engineering.
Gujarat Technological University
Bachelor of Engineering, Computer Engineering
2015 - 2019
Earned a Bachelor's degree in Computer Engineering, gaining foundational knowledge in programming, algorithms, and system design.
Tech stack
Software and tools used professionally
Apache Spark
Google Cloud Platform
Bitbucket
Kubernetes
Jenkins
Jupyter
NumPy
Pandas
PySpark
MySQL
PostgreSQL
MongoDB
Hadoop
Gmail
Node.js
Django
Databricks
OpenCV
Terraform
Jira
JavaScript
Java
TensorFlow
scikit-learn
Keras
NLTK
Kafka
Apache NiFi
Linux
macOS
Windows
Wavefront
Cloud Foundry
GraphQL
Ansible
AWS Lambda
Microsoft Excel
pytest
Airflow
SQL
Google Kubernetes Engine
XGBoost
Availability
Location
Authorized to work in
Skills
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