Data Engineer (Mid/Senior)

Razer; Singapore; On-site; SGD 70,000 - 90,000; Full time

Job summary

A leading technology company in Singapore is seeking Data Engineers to design robust data pipelines for AI applications, focusing on managing data infrastructures for model training and real-time inference. Candidates should have at least 3 years of experience in data engineering, excellent programming skills in Python and SQL, and familiarity with cloud platforms like AWS and Azure. This role offers an exciting opportunity to work closely with AI/ML teams and contributes to innovative projects in a fast-paced environment.

Qualifications

• 3+ years of experience in data engineering focused on AI/ML architectures.
• Hands-on experience in developing data pipelines for AI workloads.
• Strong analytical skills with a focus on problem-solving.

Responsibilities

• Lead AI Data Engineering initiatives and develop data pipelines.
• Design data architectures for AI model training.
• Ensure data quality, compliance, and best practices.

Skills

Python

SQL

Neo4j

Data Lake

Kubernetes

Airflow

Spark

Education

Bachelor’s or Master’s degree in computer science, Data Engineering, AI/ML

Tools

AWS

Azure

Google Cloud Platform

Terraform

Docker

DBT

Job description

Job Responsibilities :

We are looking for Data Engineers to build together 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.

Essential Duties and Responsibilities

• 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 solutions 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.

Qualifications

• 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.

*Shortlisted candidates will be contacted for assessment in due course

Are you game?