Teradata
From Teradata's careers page
Status: listed on the employer's own careers page when we last checked (daily). Confirm on their site before applying.
We offer a fast-paced, flexible, fun environment where you will have the opportunity to work on meaningful projects and face new challenges.
Our company
At Teradata, we believe that people thrive when empowered with better information. Teradata Autonomous Knowledge Platform activates enterprise intelligence by unifying data, knowledge and business context to achieve tangible outcomes. With Teradata, organizations can provide agents with full context for impact when it matters. Our solution lets businesses connect and scale on premises, in the cloud, or through a hybrid approach. Teradata delivers real business value with AI.
Our Internship Program
Our Mexico Intern program starts in September ending in March. We offer a fast-paced, flexible, fun environment where you will have the opportunity to work on meaningful projects and face new challenges. Our culture isn’t just about one kind of person. So many individuals make up who we are, making us that much more unique. This is what sets apart the dynamic, diverse, and collaborative environment that is Teradata.
You will contribute across the analytics delivery lifecycle—from understanding data and building solutions, to exploring AI capabilities that help our team work smarter.
Explore and analyze data using SQL and Python, asking business questions, spotting patterns, and turning raw datasets into clear, actionable insights for internal stakeholders.
Build and test analytics prototypes—dashboards, reports, or data models—that give teams faster access to the information they need to make decisions.
Experiment with AI and agentic tools on top of Teradata’s platform, helping automate repetitive analyst tasks and surface insights that would otherwise take days to find manually.
Validate data quality across pipelines—checking for completeness, accuracy, and consistency—and flag issues with clear documentation so engineers can act quickly.
Act as a Customer Zero advocate: use Teradata’s own autonomous knowledge platform capabilities day-to-day, compare them honestly against best-in-class tools in the market, and share structured feedback that helps shape what we build next.
Real project experience on a live analytics platform used by a global enterprise—not a training sandbox—so you graduate with work you can talk about in any interview.
A practical understanding of how AI is being applied inside a data company right now: what works, what doesn’t, and how teams make decisions about which tools to adopt.
Mentorship from senior engineers and data scientists through weekly 1:1s, regular code reviews, and a structured mid-program check-in to keep your growth on track.
A Customer Zero experience: you will have used, evaluated, and influenced Teradata’s own AI platform—giving you a rare perspective on enterprise product development that most early-career candidates simply don’t have.
You will sit on the Analytics Center of Excellence (CoE) within Teradata’s Enterprise Knowledge Platform & Intelligence Engineering organization, a cross-functional team of solutions analysts, data scientists, data engineers, data modelers, architects, and product managers who translate business needs into scalable analytics solutions. This role reports to the Director of Analytics CoE. Day-to-day, you will collaborate closely with data engineers on pipeline design, with AI/ML engineers on agent development, and with DevOps engineers on CI/CD automation—giving you broad exposure to the full analytics delivery lifecycle.
What Makes You a Qualified Candidate
Currently pursuing a bachelor’s degree in Computer Science, Data Science, or a related field
Working knowledge of SQL and Python for data analysis
Comfortable with Git and basic command-line tools
Strong communication skills in English; able to explain findings to a non-technical audience
Available for a 12–16 week hybrid internship
Curiosity about AI, large language models, or data engineering—whether through coursework, projects, or self-study
Exposure to a cloud platform (AWS, Azure, or GCP) or a data visualization tool (Tableau, Power BI)
Any experience experimenting with LLM APIs or agentic frameworks (LangChain, AutoGen, or similar)
You are genuinely curious about data and AI—you have explored tools, asked questions, or built something small just to understand how it works.
You learn by doing and are not afraid to be wrong; you ask for feedback early and iterate quickly rather than waiting for the perfect answer.
You communicate clearly and honestly—when something is confusing or unclear, you say so and ask questions rather than guessing.
You care about the quality of your work and the people who will use it, whether that’s a teammate reading your code or a stakeholder relying on your analysis.
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