Data Engineer

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

Job summary

A leading technology company in Singapore is seeking a Data Engineer to design and develop robust data pipelines for AI/ML applications. This role involves collaborating with cross-functional teams to manage data infrastructure that supports real-time AI applications. Ideal candidates will have hands-on experience in data engineering, strong programming skills in Python and SQL, and familiarity with cloud platforms. Competitive salary and professional growth opportunities offered.

Qualifications

• 1+ year of experience in data engineering, working on AI/ML-driven data architectures.
• Strong in programming languages such as Python and SQL.
• Excellent problem-solving and analytical skills, with an understanding of Gen AI technologies.

Responsibilities

• Lead AI Data Engineering initiatives by designing robust data pipelines.
• Develop high-performance data pipelines that process varied data types.
• Implement best practices for data quality, security, and compliance.

Skills

Vector/Graph; Neo4j

Data engineering

Python

SQL

Cloud infrastructure (AWS, Azure, Google Cloud)

Infrastructure as code (Terraform)

Containerization (Docker)

Container orchestration (Kubernetes)

Orchestration tools (Airflow, Prefect)

Distributed computing (Spark, Dask)

Education

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

Tools

Data Build Tool (DBT)

Data Lake

Lake House

SQL and NoSQL databases

Job description

Job Description & Requirements

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 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.

Qualifications

• Hands on experience working with Vector/Graph;Neo4j
• 1+ year 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 Docker, 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.