Internship Program

Our summer internship program lasts 10-12 weeks beginning in May/June and ending in August/September. The location for this position will be virtual as Teradata has not fully re-opened offices yet. Fast-paced, flexible, fun. The Teradata culture isn't just about one kind of person. So many individuals make up who we are, making us that much more unique. It's what sets apart the dynamic, diverse, and collaborative environment that is Teradata.

Our Team

We are the cloud incubation team, Antares if you will. What does that mean? We are responsible for marrying the Teradata database and the cloud and establishing Teradata as a leader in the cloud space. Antares focuses on aligning the relational engine to work well in the cloud. Key areas include file system, compute, storage, new kinds of nodes as well as other interesting focal points. Projects can be in such exciting areas as:

• AWS: Provisioning and using APIs, Lambdas, Fargates and other functions
• Memory management and reading and writing Parquet and other data formats
• Kafka, Kinesis and Streaming into the database
• Separation of Compute and Storage
• Automation
• Pattern matching for caching
• Database optimization
• SQL Engine enhancements

Your Opportunity

In addition to being a valued part of our group, you will also be part of a smaller, agile team composed of junior and senior engineers working in one of the workflows.

Business Objectives:

Test some or all of the following: new test assets, automation, pipelines, test frameworks, performance analysis or a combination of these.

Qualifications/Requirements

• Currently in college working towards a BS, MS or PhD in a computer related field.
• Coursework requiring development in languages such as C/C++, Python, or Go
• Coursework requiring SQL and application of RDBMS or cloud-based concepts and best practices
• Experience working in AGILE software development model through team project-based coursework.
• Quickly able to learn, leverage and incorporate new technology and methodologies on own initiative.
• Application of theoretical knowledge in interpreting data and results by systematically breaking down information in a communicable manner.