Data Engineer (8006)

TSMC•West Covina, CA

2h•$168,917 - $170,000•Onsite

About The Position

The Data Engineer will collect and manage data, and build and maintain infrastructure for storing and processing large volumes of data. The role works closely with data scientists to organize and make data available for analysis, and develops data pipelines that support extracting insights from structured and unstructured data using AI-enabled analytics. The position also works with Big Data technologies, NoSQL databases, and machine learning and deep learning algorithms to identify growth opportunities and future challenges. The position is based at TSMC Technology, Inc., 2851 Junction Avenue, San Jose, California 95134. The posted annual salary range is $168,917 to $170,000. TSMC describes its total compensation as including competitive pay, allowances, bonuses, comprehensive benefits, and development opportunities and programs. Employment is contingent on obtaining any export license or other U.S. Government approval that may be required for access to technical data subject to export control regulations.

Requirements

Master’s degree or foreign equivalent in Computer Science, Electrical Engineering, Applied Data Science, or a related field of study.
Experience with Python for data processing and machine learning workflows, including Jupyter, GitHub, and Markdown.
Experience applying machine learning and deep learning techniques to extract insights from large-scale datasets, including practical use of modern LLMs for prompt engineering, model optimization, or fine-tuning.
Experience designing data pipelines that integrate extracted and parsed data into downstream analytics or machine learning systems.
Experience extracting structured information from unstructured sources using techniques such as regular expressions, entity recognition, and LLM-based extraction, and formatting it into data structures such as lists, trees, graphs, grids, or sequences.
Experience retrieving and processing data from RESTful APIs, especially parsing and transforming semi-structured formats such as JSON and XML into data pipelines or downstream applications.

Responsibilities

Collect and manage data for further interpretation of models created by data scientists.
Create, construct, and maintain infrastructure for storing and processing large amounts of data.
Collaborate with data scientists to organize data and make it available for analysis.
Develop data pipelines that enable data scientists to extract insights from structured and unstructured data using AI-enabled analytics procedures.
Work with Big Data technologies, NoSQL databases, and machine learning and deep learning algorithms to capture growth opportunities and address future challenges.