Facilities Data Analytics Intern

Change the world. Love your job.

Texas Instruments is seeking Facilities Engineering Interns for an exciting opportunity within our global facilities organization. As a Facilities Intern, you will receive significant projects related to your major that are challenging and beneficial to the organization.

The Texas Instruments Facilities organization is responsible for managing operations at TI facilities worldwide, designing and constructing new facilities, and overseeing engineering projects to optimize processes and systems. Within the Facilities organization, the Smart Manufacturing and Automation (SMA) team focuses on long term business growth through four key areas: Cost Leadership, Quality, Technology, and Benchmarking. By leveraging industry-leading tools, methods, and processes, the team seeks to enable long-term success and establish benchmarks for performance excellence. As a Facilities Data Analytics Intern, you will play a critical role in designing and developing our data infrastructure, ensuring the accuracy, scalability, and security of our data systems.

Put your talent to work with us as a Facilities Engineering Intern!

Minimum Requirements:

• Currently pursuing a undergraduate degree in Data Engineering, Computer Engineering, Computer Science, or related degree

• Cumulative 3.0/4.0 GPA or higher

Preferred Qualifications:

• Strong foundation in database mgmt. and Architecture strategies (Relational, Document & Graph)

• Proficiency in SQL, Python, R, Javascript, etc.

• Experience with statistics, algorithm development, and data visualization

• Demonstrated analytical and problem-solving skills

• Strong verbal and written communication skills

• Ability to work in teams and collaborate effectively with people in different functions

• Strong time management skills that enable on-time project delivery

• Ability to work effectively in a fast-paced and rapidly changing environment

• Ability to take the initiative and drive for results

• Ability to build strong, influential relationships