Senior Data Engineer

Joining Razer will place you on a global mission to revolutionize the way the world games. Razer isa 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 alsoa 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 :

• Lead AI Data Engineeringinitiatives by driving the design and development of robust data pipelines for AI/ML workloads, ensuring efficiency, scalability, and reliability. 

• Design and implement data architectures that support AI model training, including feature stores, vector databases, and real-time streaming solutions. 

• Develophigh performancedatapipelinesthat process structured, semi-structured, and unstructured data at scale, supporting the various AI applications 

• Implement best practices for data quality, lineage, security, and compliance for AI applications 

• Develop automated data workflows, integrate withDevOps,MLOps frameworks, and enable model reproducibility through efficient data management. 

• Continuously explore advancements in AI data engineering, including distributed computing, data mesh architectures, and next-gen storage solution that best fit the various AI initiatives 

• Work closely with data scientists andAI/ML engineers tooptimize feature extraction, data labeling, and real-time inference pipelines

Pre-Requisites :

• Hands on experience working with Vector/Graph;Neo4j

• 3+years of experience in data engineering, working on AI/ML-driven data architectures 

• Ability to work in fast paced, high pressure, agile environment. 

• Ability and willingness to learn any new technologies and apply them at workin order to stay ahead. 

• Strong in programming languages such asPython, SQL. 

• Experience in developing and deploying applications running on cloud infrastructure such as AWS, Azure or Google Cloud Platform using Infrastructure as code tools such as Terraform, containerization tools like Dockers, container orchestration platforms like Kubernetes 

• Experience using orchestration tools like Airflow or Prefect, distributed computing framework like Spark orDask, data transformation tool like Data Build Tool (DBT) 

• Excellent with various data processing techniques (both streaming and batch), managing andoptimizing data storage (Data Lake, Lake House and Database, SQL, and NoSQL) is essential. 

• Experience in network infrastructure,real-time AI inferencing pipelines using event-driven architectures 

• Excellent problem-solving and analytical skills, with an understanding of Gen AI technologies and their applications 

• Excellent written and verbal communication skills for coordinating across teams. 

• Experience and Interest to keep up with the advancement in the Data Engineering Field 

Education & Experience 

• Has aBachelor’s orMaster’s degree in computer science, Data Engineering, AI/ML, or a related fieldfrom an accredited institution 

Travel Requirements 

• Role based in​Singapore office​ and may require up to 1 travel trip per year

Are you game?