Data Engineer Real-Time

NGUYEN TIEN TOAN

Data Engineer

+Phone: 038*******

+Email: ******************@*****.***

+Github: https://github.com/nguyentientoanhaui

About

Leverage my knowledge in data and

programming skills in a practical environment,

aiming to learn, grow, and make meaningful

contributions as a data engineer by supporting

efficient data processing and adding value to

the organization.

Skills & Competencies

I. Project

1. Kafka to Hadoop

Description: This project simulates the collection and processing of sales transaction data for Company A from various branches across the country. It uses Apache NiFi, Apache Kafka, and Hadoop HDFS to build a real-time data storage pipeline. Simulated Scenario: Collect sales transaction data from branches and integrate real-time flight data from the Aviationstack API, allowing continuous processing and providing timely information to support business decision-making. Technologies Used:

• Apache NiFi

• Apache Kafka

• Hadoop HDFS

• MongoDB

• Aviationstack API.

Outcome: Provide a continuous and efficient data processing solution to support business decisions based on big data analytics.

Github: https://github.com/nguyentientoanhaui/Kafka-to-Hadoop MySQL, MongoDB

English: Upper Intermediate)

Ubuntu operating system

2. Predict results with continuous data streaming

Description: Developed a real-time credit card fraud detection system in a simulated transaction environment. Transaction data is continuously streamed to Apache Kafka, where an AI model detects potential fraudulent activities with high accuracy. Technologies Used:

• Data Streaming: Apache Kafka

• Machine Learning: AI model for fraud detection

• Storage: MongoDB for stable data storage

• Data Pipeline: Real-time data processing and integration with Kafka Outcome: Achieved real-time detection and secure storage of fraudulent transaction predictions, enabling timely insights and integration with other systems for enhanced business decision-making.

Github: https://github.com/nguyentientoanhaui/Predict-results-with-continuous-data- Streaming-

3. Data Crawling

Description: Developed a data crawling system to collect product data from the ShopeeFood API for market analysis.

Technologies Used:

• Programming: Python

• Libraries: Requests, Pandas

• Storage: MongoDB

• Multithreading: Improved data collection performance

• Scheduling: Set up a weekly process to push data from MongoDB to Hadoop Outcome: Collected and stored thousands of product details from ShopeeFood, providing a database for analysis and business decision-making. Github: https://github.com/nguyentientoanhaui/data_crawling II. Certifications

• SIC (Samsung Innovation Campus for Big Data)

• TOEIC: 735

III. Education

Hanoi University of Industry, B.Sc. in Information Technology (2021-2025)

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