Top Data Engineer Jobs in Singapore

Design, build, and ship agentic AI applications that answer business questions over governed data. Implement RAG, NL-to-query, tool/function calling, and evaluation/guardrails. Partner with data teams on metrics, models, pipelines, and apply strong data governance and security for financial services.

The IT Engineer (Data Services) is responsible for managing and optimizing database systems, ensuring data availability, performance, and compliance, while also developing automated solutions and collaborating with site customers.

The role focuses on developing product disposition solutions, enhancing yield and reliability through data analysis, and mentoring team members while collaborating across teams.

The role involves ensuring end-to-end performance and power readiness of Data Center SSD programs through technical execution, analysis, and leadership across teams.

Design, build, and productionize GenAI and ML solutions for semiconductor engineering: large-scale data pipelines, LLM/RAG and agentic workflows, model training/inference, analytics, deployment, monitoring, and cross-functional collaboration to improve quality, cost, and engineering productivity.

This role focuses on improving productivity in labor operations through program management, data analysis, and implementing AI and automation solutions.

The role involves leading data analytics initiatives to improve yield and quality, developing algorithms, enhancing data infrastructure, and collaborating with cross-functional teams to drive innovation in HBM product engineering.

Develop and maintain data pipelines and ETL processes, optimize data structures, and enhance data solutions using AI in a Cloud environment.

Develop and deploy product-disposition solutions using data analysis, machine learning, and AI to improve yields and reliability. Mentor team members and collaborate across functions to drive innovation and enhance product quality.

The role involves developing advanced data analytics solutions for yield and quality improvement in HBM product engineering, collaborating with cross-functional teams and driving innovation in AI and machine learning.

The IT Engineer (Data Services) is responsible for database system management, performance tuning, compliance, incident resolution, and automation of database operations.

The role involves developing AI-driven solutions for semiconductor engineering, focusing on GenAI systems, data pipelines, and machine learning models while collaborating with cross-functional teams.

Responsible for building and maintaining data pipelines, optimizing data structures, and developing ETL processes with AI support for data analytics applications.

The role involves developing data solutions and ETL processes, optimizing data structures, and incorporating AI to enhance data analytics and engineering.

The Data Engineer will optimize data infrastructure, develop scalable ETL processes, establish data governance, and collaborate with data teams to ensure data accuracy and performance.

As a Data Engineer, you'll design and develop cloud-native data platforms, create scalable data pipelines, and support analytics and reporting across teams.

As a Data Engineer, you will develop and manage data pipelines, ensuring reliable data ingestion and delivery while optimizing for simplicity and performance.

The Data Engineer will optimize data architecture, improve data flow for teams, and support analytics initiatives with large data sets.

The Data Engineer designs and maintains data architectures and pipelines, processes datasets, optimizes ETL processes, and collaborates with teams to support data-driven decisions.

Develop and deploy product-disposition workflows and deviation alert systems using statistical tools and ML/AI to improve yield, reliability, and quality. Build algorithms for data mining, pattern recognition, and wafer/die screening. Collaborate with Fab, design, and quality teams, mentor team members, and drive technical innovation to meet KPIs like quality, cost, cycle time, and scale.

Design, build, and optimize offline and real-time data pipelines and warehouses for product data. Lead end-to-end R&D for online product data pipelines, ensure timeliness and accuracy, perform Flink-based real-time processing and performance tuning, and enable business growth through data products and services.

Build and maintain regional data pipelines and architecture, automate ETL and reporting, transform data for analytics, and collaborate with business stakeholders to identify data gaps and implement solutions. Share best practices and support dashboard/report automation.

Design, implement, and maintain data-driven processes and analytics solutions. Collect, cleanse, automate, and prepare data from disparate sources. Build KPIs and dashboards, apply statistical and machine learning methods, collaborate with stakeholders, perform testing and deployment, and train users to enable data-driven decision making and process improvements.

Manage, maintain, and optimize critical database systems (SQL Server, Oracle). Perform installs, patches, backups, access control, monitoring, performance tuning, incident/change/problem management, on-call support, capacity planning, automation, reporting, and collaborate with global teams and site stakeholders.

Lead architecture, development, and operation of Airwallex's data and AI platforms. Drive company-wide data platform solutions, build scalable multi-region pipelines, enforce governance and security, mentor the team, advocate best practices, and influence technical roadmaps to enable AI/ML-driven business impact.