New College Graduate - Data Engineer
Texas Instruments
Change the world. Love your job.
In your first year with TI you'll join the Career Accelerator Program (CAP) – a development experience that blends professional skill workshops, technical training and on the job learning. The program is tailored to your educational background and experience level, ensuring you can start delivering real world data engineer impact from day 1, whether you're working on foundational data pipelines or cutting-edge AI-driven solutions.
About the job:
As a Data Engineer, you will play a key role in building and maintaining the data infrastructure and systems that power AI/ML, analytics, reporting, and data-driven decision-making across the organization. You will be part of a cross-functional team, gaining hands-on experience working with modern data tools and cloud technologies while transforming raw data into actionable insights through collaboration with engineers and business stakeholders.
In this role, you will also have the opportunity to architect and lead the deployment of large-scale data engineering solutions, pioneering AI-driven data processing frameworks that integrate transformer-based LLMs, deep learning models, and traditional machine learning algorithms.
Key Responsibilities:
- Develop and maintain scalable data pipelines and ETL/ELT workflows for ingesting, processing, and transforming large datasets from multiple sources
- Build and optimize data models, schemas, and databases to ensure efficient data storage, accessibility, and performance
- Perform data cleaning, validation, and quality checks to deliver accurate and reliable data for analytical use
- Work with SQL, Python, and modern data tools such as Spark to automate data flows and support data science initiatives
- Architect and implement large-scale data engineering solutions across hybrid cloud environments
- Build reusable libraries and automated pipelines while applying software engineering best practices such as CI/CD, testing and monitoring
- Collaborate with analysts, engineers, and business teams to understand data requirements and deliver solutions
- Monitor data infrastructure performance and troubleshoot issues as needed
- Maintain documentation for pipelines, data models, and transformation logic
- Forecast emerging data needs, define design standards and drive strategic upgrades to storage and processing infrastructure
- Stay updated on emerging data technologies and recommend improvements to data architecture
Texas Instruments will not sponsor job applicants for visas or work authorization for this position.
- Engineer your future. We empower our employees to truly own their career and development. Come collaborate with some of the smartest people in the world to shape the future of electronics.
- We're different by design. Diverse backgrounds and perspectives are what push innovation forward and what make TI stronger. We value each and every voice, and look forward to hearing yours. Meet the people of TI
- Benefits that benefit you. We offer competitive pay and benefits designed to help you and your family live your best life. Your well-being is important to us.
TI does not make recruiting or hiring decisions based on citizenship, immigration status or national origin. However, if TI determines that information access or export control restrictions based upon applicable laws and regulations would prohibit you from working in this position without first obtaining an export license, TI expressly reserves the right not to seek such a license for you and either offer you a different position that does not require an export license or decline to move forward with your employment.
Minimum Requirements:
- Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, Data Science, or related field of study
- Cumulative 3.0/4.0 GPA or higher
Preferred Qualifications:
- Master's degree and/or PhD in Electrical Engineering, Computer Engineering, Computer Science, Data Science, or related field
- Proficiency in programming languages such as Python, Java, Scala, C/C++ and strong SQL skills for data manipulation and querying
- Understanding of ETL processes, database concepts, and experience with big data platforms (e.g., Spark), cloud services (AWS, Azure, or GCP)
- Experience with AI/ML frameworks (e.g., PyTorch) and large-scale data processing, including transformer-based LLMs and neural networks
- Knowledge of machine learning algorithms ranging from traditional ML to cutting-edge deep learning models
- Strong analytical and problem-solving abilities with experience tackling complex, multifaceted challenges
- Exposure to or proven experience in machine learning, deep learning concepts, NLP, computer vision, speech, and time series analysis
- Demonstrated ability to develop end-to-end data pipelines, AI-enabled data tools, or enterprise-scale data architecture solutions
- Publications or conference presentations in AI/ML or data engineering topics
- Proven teamwork and communication skills in multidisciplinary projects, including ability to present technical concepts to non-technical stakeholders
- Strong time management and project management skills that enable on-time delivery of high-impact projects
- Demonstrated ability to build strong, influential relationships and leadership in cross-functional team environment
- Ability to work effectively in a fast-paced and rapidly changing environment with strong initiative and adaptability
- Ability to take initiative, drive for results, and drive innovation