Data Engineer (7747)

TSMC•San Jose, CA

4d•Onsite

About The Position

TSMC Technology, Inc. is seeking a Data Engineer to collect and manage data, facilitating further interpretation of the model created by data scientists. The role involves creating, constructing, and maintaining the essential infrastructure for storing and processing vast amounts of data. The Data Engineer will collaborate closely with data scientists to ensure data is correctly organized and available for analysis. Additionally, the position requires developing data pipelines for data scientists to extract insights from structured and unstructured data using AI-enabled analytics procedures. The role will also involve working with Big Data technologies, NoSQL databases, machine learning and deep learning algorithms to capture profitable growth opportunities and future challenges.

Requirements

Master’s degree or foreign equivalent in computer science, information systems management, information science or related field, and one ( 1 ) year of experience in a related position
Knowledge of Python
Experienced with Git-based version control systems and Markdown for documentation
Experience connecting to REST API endpoints, particularly in parsing data in JSON and XML formats
Experience applying web scraping techniques and data extraction methods using Python tools such as Scrapy, BeautifulSoup, and Selenium
Experience with front-end web technologies (HTML, CSS) for data visualization and prototype development
Experience in finance, accounting, and market analysis
Experience in data pipeline/workflow design, involving data extraction, transformation, and system integration across structured and unstructured data sources across multiple systems

Responsibilities

Collect and manage data, facilitating further interpretation of the model created by data scientists.
Create, construct, and maintain the essential infrastructure for storing and processing vast amounts of data.
Collaborate closely with data scientists to ensure that the data is correctly organized and available for analysis.
Develop data pipelines for data scientists to extract insights from structured and unstructured data using AI-enabled analytics procedures.
Work with Big Data technologies, NoSQL databases, machine learning and deep learning algorithms to capture profitable growth opportunities and future challenges.