Senior Data Engineer

Singaporesenior

Data EngineerData

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Key Responsibilities

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Data EngineerData

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.

Responsibilities

~2 min read

We are looking for a Senior Data Engineer to lead the technical initiatives for AI Data Engineering, enabling scalable, high-performance data pipelines that power AI and machine learning applications. This role will focus on architecting, optimizing, and managing data infrastructure to support AI model training, feature engineering, and real-time inference. You will collaborate closely with AI/ML engineers, data scientists, and platform teams to build the next generation of AI-driven products.

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

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

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Develop high performance data pipelines that process structured, semi-structured, and unstructured data at scale, supporting the various AI applications

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

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

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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

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Work closely with data scientists and AI/ML engineers to optimize feature extraction, data labeling, and real-time inference pipelines

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 work in order to stay ahead.

Strong in programming languages such as Python, 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 or Dask, data transformation tool like Data Build Tool (DBT)

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