Top Data Engineer Jobs in Singapore

Design and implement scalable data infrastructure, optimize data pipelines, ensure data quality, and collaborate across teams for strategic insights.

The Data Project Engineer coordinates internal and external projects, assists teams with follow-ups, and performs data analysis and troubleshooting tasks.

Manage patent data operations, analyze data requirements, ensure data quality, optimize processing frameworks, and collaborate on architecture upgrades.

The Senior Data Engineer builds and maintains data infrastructure, develops data processing pipelines, collaborates on data models, and ensures data quality and governance.

The Data Engineer will analyze and prototype features for AML data, ensuring data quality and collaborating with teams to enhance compliance efforts.

The Software Engineer will enhance data collection for model training, manage and operate cloud infrastructure, and collaborate on dataset strategy.

The Senior Data Engineer will build scalable data pipelines, collaborate with teams to optimize data processes, and ensure data quality and governance.

The Senior Data Engineer will design and implement data architectures for AI/ML applications, lead data initiatives, and optimize data pipelines for efficiency and reliability.

The role requires operating and optimizing global data platform components, implementing automation, and enhancing data pipeline resiliency using DevSecOps methodologies.

Design and manage Big Data and Kafka infrastructures, optimize performance, ensure security, and lead a team of SRE engineers while promoting operational excellence.

The role involves developing and maintaining data systems for overseas advertising, conducting data analysis, and optimizing business operations based on insights.

The Big Data Test Engineer will ensure quality of big data solutions through testing, validating data pipelines, and collaborating with data engineers.

Develop and maintain scalable data pipelines using Python and AWS, collaborating with teams to enhance data accessibility and quality. Participate in DevOps practices to optimize data integration with AI services.

Design and implement large scale data processing pipelines, mentor junior engineers, and maintain cloud-based data platform infrastructure.

Oversee Tencent's big data platforms for stability, assist users with issues, optimize workflows, develop tools, and reduce costs.

The Cloud Data Platform Engineer designs, builds, and maintains data infrastructure on Azure and Snowflake, optimizing for performance, security, and scalability while collaborating with cross-functional teams.

Develop and implement computer vision algorithms, evaluate model performance, and integrate solutions into larger systems, while maintaining documentation and staying updated on technology advances.

The Senior Data Engineer will lead AI Data Engineering initiatives, architect and manage data infrastructure, and optimize data pipelines for AI and ML applications using various tools and technologies.

Responsible for building and maintaining data reports and systems for overseas advertising, conducting data analysis, and providing business optimization insights.

The Senior/Lead Data Engineer will design, develop, and optimize data solutions on Alibaba Cloud, managing data pipelines and warehouses, ensuring data quality, and collaborating with teams.

Lead Data Engineering efforts, mentor a team, architect scalable data solutions, collaborate with stakeholders, optimize data workflows, and ensure best practices in a cloud environment.

Design and maintain scalable data platforms on AWS and Databricks, focusing on efficient data processing, analytics, and orchestration of pipelines.

As a Senior Data ETL Engineer, you'll develop data pipelines, support AI/ML initiatives, ensure data quality, and optimize performance.

Lead initiatives to enhance yield and quality in HBM product engineering through advanced data analysis and machine learning, collaborating across teams and mentoring members.

The role involves architecting and maintaining AI and data platforms, optimizing data pipelines and APIs, and ensuring system scalability.