Senior Data Engineer

Razer is hiring a Senior Data Engineer in Singapore, Singapore. Level rates it ; you can apply on Razer.

Level's read on this job

On Level's scale, this data engineer role is Builds AI ●●●●: the job is building AI systems.
Tools and skills the posting cites include MLOps and AI data labeling.
Level classifies it as a senior role.
Level lists 148 other open roles at Razer.

AI in this role

ml-opsai-data-labeling

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 :

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.

Lead AI Data Engineering initiatives 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.

Develop high performance data pipelines that 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 with DevOps, 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 and AI/ML engineers to optimize 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 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.

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 a Bachelor’s or Master’s degree in computer science, Data Engineering, AI/ML, or a related field from an accredited institution

Travel Requirements

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

Are you game?

How we rate this

Senior Data Engineer at Razer rates 88 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Senior Data Engineer is an open job at Razer.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in Singapore.
The job was posted on April 17, 2025.
Seniority: senior.
Applications are handled by Razer. Apply on Razer

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

ML OpsAI Data Labeling

Also common in data engineer jobs at this level

LLM RAG AI agents Docker LangChain PyTorch

Pay

Typical data engineer job: $150k

This posting doesn't list pay. Use the typical data engineer figure when pay comes up. See data engineer jobs

Questions you could be asked

How do you monitor a model once it's live, and how do you know it needs retraining?
How do you keep labeling instructions consistent across a large annotation team?
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

List these exact terms on your resume: ML Ops and AI Data Labeling. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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