Top Data Engineer Jobs in Singapore

Design, build, test, deploy, and maintain scalable, resilient cloud-based data pipelines and microservices (primarily on AWS). Implement ETL/ELT, data lake/warehouse solutions, support analytics integration, enforce data quality, and follow Agile DevOps practices with CI/CD and IaC.

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.

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

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

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.

Design, build, and maintain scalable data pipelines and ETL processes. Ensure data quality, lead data migrations and processing, advise on data architecture, optimize pipelines, shape best practices, collaborate across teams, and lead stakeholder communications to solve complex data challenges.

Design, develop, and maintain scalable data solutions and pipelines. Ensure data quality, lead ETL/migration efforts, provide architecture and optimization guidance, collaborate with cross-functional teams, and influence data strategy and best practices.

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.

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.

Design and build scalable batch and streaming ETL pipelines and data models, collaborate with stakeholders to translate data needs, ensure data quality and governance, and own end-to-end delivery for Knowledge Platform initiatives in Singapore.

Lead architecture, development, and operation of Airwallex's data and AI platforms. Drive company-wide data platform strategy, build scalable multi-region data pipelines, promote best practices, mentor engineers, and enable data-driven decision making and AI readiness across the organization.

Design and build scalable batch and streaming ETL pipelines and data models. Partner with engineers and business stakeholders to deliver reliable SSOT data, ensure data quality, governance, and support ML/AI use cases. Own end-to-end pipeline design, monitoring, and ongoing 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 design and implementation of process-mining and labor data engineering for Front End operations. Build digital footprint capabilities, dashboards, AI-driven optimizations, and standardized processes to drive labor productivity, savings, and scalable operational improvements across global sites.

Assist in building and maintaining data ingestion pipelines and storage for AI workflows. Implement deployment, security, and monitoring for applications; collaborate with stakeholders and design teams; test and validate data verification and AI workflows; document solutions and follow best practices while continuously learning new tools.

Design, build, and maintain scalable data pipelines, data lakes, and databases; ingest and map customer financial datasets; monitor pipeline reliability; translate business requirements into data flows and analytical insights to ensure high-quality, usable data.

Drive labor productivity through program management, data analysis, automation, and AI methodologies to enhance operational efficiency and reduce labor hours.

Design, develop, and deploy large-scale data systems to support cybersecurity products for threat detection, investigation, and analysis. Build scalable, high-availability architectures, microservices, and RESTful APIs with CI/CD. Monitor system health and telemetry, scale systems for growing data volumes, and collaborate with cross-functional teams to meet operational needs.

Lead design and development of scalable data infrastructure and self-service tooling for data engineering teams. Provide technical leadership, implement robust systems (Kubernetes/Terraform/GitOps), ensure quality through testing and maintenance, troubleshoot production issues, and collaborate cross-functionally to deliver reliable data platforms.

Lead design and build of high-performance distributed data infrastructure and AI enablement platforms. Optimize systems internals and JVM performance, implement lakehouse and real-time streaming, develop scalable vector indexing and AI knowledge platform, own SDLC for petabyte-scale systems across global regions, drive engineering best practices, and mentor mid-level engineers.

Lead design, build, and operate distributed, large-scale (batch/streaming) data platforms and pipelines. Drive technical decisions, performance optimization, data architecture (lakehouse), tooling standards, third-party integration, and mentor junior engineers to enable company-wide data-driven capabilities.

As a Data Engineer at SHOPLINE, you'll be responsible for managing payments data, enhancing data quality, and constructing business evaluation metrics while collaborating across functions.