Data Engineer (Intern)

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 Scope

You will be responsible for developing and implementing data pipelines, storage systems, and backend application software to power GenAI capabilities. This includes designing and building high-volume backend data processing systems that support Razer’s cutting-edge Artificial Intelligence (AI) gaming products.
 

Job Responsibilities

• Design and build data systems to store, process, and analyze large-scale data for GenAI use cases, following industry best practices in Data Warehousing.

• Manage data lakes, databases, and knowledge bases, including SQL schema design, tokenization techniques

• Create and template robust data pipelines for high-volume ETL from API and web sources, with orchestration using Airflow and infrastructure deployment via Terraform.

• Develop and maintain scalable, high-performance backend systems to support evolving product needs, using AWS cloud technologies and CI/CD practices for seamless code integration and deployment.

• Collaborate with stakeholders to gather technical requirements and translate them into end-to-end data pipeline solutions.

Pre-Requisites

• Currently pursuing a degree in Computer Science or any related field, with a strong interest in Data Engineering and Analytics.

• Experience working with Retrieval-Augmented Generation (RAG) for LLM applications

• Strong knowledge of data engineering, with proficiency in Python, SQL, and API-based data services

• Skilled in system design and building scalable, high-concurrency applications

• Hands-on experience with data processing techniques (streaming, batch, event-driven) and optimizing data storage solutions (Data Lakes, Vector Databases, SQL/NoSQL)

• Proficient in deploying applications on cloud platforms (AWS, Azure, GCP) using Infrastructure as Code (e.g., Terraform), Docker, and Kubernetes

• Familiar with cloud-native tools and services from AWS or GCP

• Creative, self-driven, and able to work independently in an agile environment

Are you game?