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Razer Inc. is a global consumer electronics and technology company specializing in high-performance hardware, software, and digital services designed specifically for gamers and content creators. Founded in 2005 by Min-Liang Tan and Robert Krakoff, the company is dual-headquartered in Irvine, California, and Queenstown, Singapore.

Joining Razer will place you on a global mission to revolutionize the way the world games. Razer is a place to do great work, offering you the opportunity to make an impact globally while working across a global team located across 5 continents. Razer is also a great place to work, providing you the unique, gamer-centric #LifeAtRazer experience that will put you in an accelerated growth, both personally and professionally.

Job Responsibilities :

Join our Big Data team as an AI Data Engineer Intern and help power the data foundation behind advanced analytics and AI/ML solutions. This role sits at the intersection of data engineering, cloud infrastructure, and artificial intelligence.

You will collaborate closely with data engineers, data scientists, analytics engineers, and data product managers to design, optimize, and scale modern data pipelines that fuel AI models, business intelligence, and data-driven decision-making across the organization.

This internship offers hands-on experience with real production systems, modern data stack technologies, and to create AI-enabled workflows in a cloud-native environment.

Pre-requisites:

  • Strong interest in Data Engineering, Cloud Technologies and AI/ML applications
  • Proficiency in Python, SQL.
  • Exposure to cloud technologies (Amazon Web Services, Google Cloud Platform)
  • Exposure to orchestration tools (Airflow)
  • Exposure to business intelligence tool (Superset, PowerBI, Tableau)

• Ability to work independently and collaboratively in a fast-paced environment.

Learning Objectives:

By the end of the internship, you will gain practical experience in building AI-ready data systems using industry best practices and modern data technologies.

Learning Outcomes:

  • Modern Data Warehousing & Lakehouse Architecture in the cloud (AWS)
  • Pipeline Design Patterns using ELT
  • Data transformation tools (DBT)
  • Infrastructure as Code (Terraform)
  • Workflow orchestration (Airflow)
  • CI/CD for Data Engineering
  • Spec driven development for data engineering
  • Performance Optimization & Data Quality Engineering
  • Documentation and communication of technical solutions
  • Collaboration with data engineers, analytics engineers, data analysts, data scientists

Pre-Requisites :

Razer is proud to be an Equal Opportunity Employer. We believe that diverse teams drive better ideas, better products, and a stronger culture. We are committed to providing an inclusive, respectful, and fair workplace for every employee across all the countries we operate in. We do not discriminate on the basis of race, ethnicity, colour, nationality, ancestry, religion, age, sex, sexual orientation, gender identity or expression, disability, marital status, or any other characteristic protected under local laws. Where needed, we provide reasonable accommodations - including for disability or religious practices - to ensure every team member can perform and contribute at their best.

Are you game?

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