Senior Data Engineer

Razer; Singapore; On-site; SGD 80,000 - 120,000; Full time

Job summary

A leading technology company in Singapore is seeking a Senior Data Engineer to lead AI Data Engineering initiatives. The role involves architecting and managing scalable data infrastructure for AI applications. Candidates must have 3+ years of experience, strong programming skills in Python and SQL, and familiarity with cloud technologies. Join a dynamic team and contribute to the future of AI-driven products.

Qualifications

• 3+ years of experience in data engineering, particularly with AI/ML architectures.
• Ability to work in a fast-paced, high-pressure environment.
• Experience in developing and deploying cloud applications.

Responsibilities

• Lead the design and development of robust AI/ML data pipelines.
• Implement data architectures supporting AI model training.
• Develop automated data workflows integrated with DevOps and MLOps.

Skills

Vector/Graph;Neo4j

Programming in Python

SQL

Data processing techniques

Experience with AWS, Azure, GCP

Orchestration tools like Airflow/Prefect

Distributed computing frameworks (Spark/Dask)

Data transformation tool (DBT)

Real-time AI inferencing

Education

Bachelor’s or Master’s degree in Computer Science

Tools

Terraform

Docker

Kubernetes

Terraform

Docker

Kubernetes

Airflow

Spark

Data Build Tool (DBT)

Neo4j

Job description

Job Responsibilities

We are looking for Senior Data Engineers 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.

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.

Pre‑Requisites

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.