Information Technology Intern – Data Engineering

Texas Instruments•Dallas, TX

About The Position

As a Data Engineering intern, you'll 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. And, you'll 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.

Requirements

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

Nice To Haves

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

Responsibilities

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