Data Engineer Warehouse

VAMSI KRISHNA BUNGA

• New York, NY • linkedin.com/in/vamsikrishna20 • +1-347-***-**** • *.*****@***.*** EDUCATION

New York University New York, NY

Master of Science in Computer Engineering (GPA 4.0/4.0) May 2024 Relevant Coursework: Data Structures and Algorithms, Machine Learning, Big Data, Cloud Computing Andhra University Visakhapatnam, India

Bachelor of Technology in Electronics and Communication Engineering (GPA 3.9/4.0) Aug. 2016 – Jul. 2020 EXPERIENCE

Tesla, Inc. Fremont, CA

Data Engineer Intern Jan. 2024 – May 2024

• Developing Kafka-streaming ETLs for near real-time replication of data from MySQL to Tesla's data warehouse, ensuring executive dashboards update within 20 seconds.

• Playing a key role in Tesla's data warehouse migration from Vertica to ClickHouse to enhance query performance and reduce costs by 40% with open-source adoption. Phenom People Hyderabad, India

Data Engineer Jul. 2020 – Jul. 2022

• Orchestrated and built an Apache Airflow based batch processing ETL pipeline, ensuring seamless data transformations and robust validation checks before data ingestion.

• Improved query performance and reduced processing time of a data pipeline by 30% by revamping the architecture and database design.

• Reduced load time by 10 times by migrating backend database from PostgreSQL to Amazon Redshift while utilizing its Massively Parallel Processing Architecture.

• Enabled real-time analytics by building an Apache Kafka based Change Data Capture (CDC) service with Debezium and AWS Lambda to replicate MongoDB data to S3 bucket.

• Lowered customer onboarding time by 40% by collaborating with a team of 5 to design and build an automated job scheduler to retrieve files from SFTP server as soon as they are created. PROJECTS

Serverless Dining Concierge Chatbot Sept. 2023 – Oct. 2023

• Implemented a serverless Dining Concierge chatbot with AWS technologies (S3, Lambda, API Gateway, Lex), providing tailored restaurant suggestions.

• Integrated DynamoDB and Elasticsearch for efficient data handling and retrieval within a microservice-driven application architecture.

• Implemented automated suggestion delivery and email notifications using AWS SES, enhancing user engagement with personalized interactions.

Efficient Image Classification for Resource-Constrained Devices Mar. 2023 – Apr. 2023

• Proposed a modified ResNet architecture for image classification tasks, with the goal of reducing the number of trainable parameters while maintaining acceptable accuracy.

• Aimed to develop a more efficient image classifier suitable for deployment on resource-constrained devices, such as Internet of Things (IoT) devices.

• Achieved a test accuracy of 93.4% on the CIFAR-10 dataset, with just 2.79 million trainable parameters, representing a substantial reduction compared to the original ResNet architecture. SKILLS

Programming: Data Structures and Algorithms, Python, C, C++, Java, SQL, object-oriented design, JavaScript. Technologies: Airflow, Kafka, Spark, REST API Design, PyTorch, AWS, Amazon Redshift, Amazon S3, AWS Lambda, DynamoDB, MySQL, PostgreSQL, MATLAB, Django, Spring Boot, Docker, Kubernetes, Linux, MongoDB, NoSQL, Data Warehousing, Data Lake, Distributed and Parallel Systems, ETL, Git.

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