Data Engineering Intern

Job Description

As a Data Engineering intern, you will help build the data infrastructure that powers TI's AI/ML initiatives, analytics, and data-driven decision-making across the organization. You'll work with cutting-edge data technologies and cloud platforms, gaining hands-on experience in transforming raw data into actionable insights. You'll also have the opportunity to work in exciting areas like machine learning pipelines, big data processing, AI-driven analytics, cloud data architecture, real-time data streaming, and automated data workflows.

Responsibilities

• Assist in the development and maintenance of data pipelines and ETL/ELT workflows for processing datasets from multiple sources.
• Support the building and optimization of data models, schemas, and databases to ensure efficient data storage and accessibility.
• Participate in data cleaning, validation, and quality checks to help deliver accurate and reliable data for analytical use.
• Work with SQL, Python, and modern data tools such as Spark to support data flows and data science initiatives.
• Collaborate with data engineers and business teams to understand data requirements and contribute to solution development.
• Assist in monitoring data infrastructure performance and help troubleshoot issues as needed.
• Contribute to documentation for pipelines, data models, and transformation logic.
• Learn about emerging data technologies and support recommendations for data architecture improvements.
• Support the implementation of software engineering best practices such as testing and monitoring in data workflows.

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

Texas Instruments will not sponsor job applicants for visas or work authorization for this position.

Qualifications

Minimum Requirements

• Currently pursuing an undergraduate or graduate degree in Electrical Engineering, Computer Engineering, Computer Science, Data Science, or a related field.
• Cumulative 3.0/4.0 GPA or higher.

Preferred Qualifications

• Coursework or project experience with programming languages such as Python, Java, or SQL.
• Basic understanding of database concepts and data manipulation.
• Exposure to big data platforms (e.g., Spark), cloud services (AWS, Azure, or GCP), or machine learning concepts through coursework or personal projects.
• Ability to establish strong relationships with key stakeholders critical to success, both internally and externally.
• Strong verbal and written communication skills.
• Ability to quickly ramp on new systems and processes.
• Demonstrated strong interpersonal, analytical, and problem-solving skills.
• Ability to work in teams and collaborate effectively with people in different functions.
• Ability to take the initiative and drive for results.
• Strong time management skills that enable on-time project delivery.