Top Data Engineer Jobs in Singapore

Design and implement data models, build ETL pipelines, manage data quality and governance, and leverage AI in data engineering.

The role involves designing and optimizing a next-generation data platform, developing large-scale data processing systems, and mentoring junior engineers while ensuring high-quality software engineering practices.

The (Senior) Data Platform Engineer will design and build data pipelines, manage data infrastructure, and ensure data quality and consistency across the Growth Data Platform.

As a Senior Data Platform Engineer, you will design and optimize data infrastructure, develop data processing systems, and mentor junior engineers to drive data-driven initiatives.

As a Senior Software Engineer in Data & AI Infrastructure, you will develop scalable data solutions, manage systems like Kafka and Spark, ensure compliance with security policies, and collaborate with cross-functional teams.

As a DevOps Engineer, you'll design and maintain cloud infrastructure for data engineering, improve operational capabilities, and build consensus on practices among global teams.

In this data engineering role, you will design, build, and maintain scalable data pipelines, collaborate with teams, and improve data platform efficiency.

Design and implement scalable data models, manage ETL pipelines, ensure data governance, and collaborate across teams to address complex data challenges.

Seeking a Data Engineer with 4-6 years of experience in big data technologies, data pipelines, and databases, mainly in the financial services sector.

Design and architect scalable backend services, develop robust governance systems, build SaaS solutions, and mentor junior engineers to enhance IoT platform capabilities.

The Data Engineer will solve complex data challenges, optimize production data pipelines, enhance database performance, and ensure data accuracy for decision-making.

Lead the architecture and development of data and AI platforms for Airwallex, mentoring teams and advocating for best practices. Engage in hands-on problem resolution and drive data-driven decision-making across the company.

The Senior Data Engineer develops and maintains scalable data infrastructure and pipelines, ensuring data quality and accessibility for data-driven decision-making.

Oversee operations of big data platforms, monitor services, manage configurations, address vulnerabilities, and develop automation scripts for operational consistency.

Develop and maintain data pipelines, support data collection, build datasets for AI evaluation, and create dashboards for monitoring product metrics.

As a Data Engineer (Compliance), you will manage SQL scripts for compliance monitoring, handle data governance, and ensure regulatory compliance while collaborating with various stakeholders.

As a Data Engineer at Xtremax, you'll design, build, and maintain data pipelines, collaborate with various teams, and transform data for analytics.

The Senior DevOps Engineer will lead DevOps strategy, manage cloud infrastructure, enhance data tools, and ensure operational stability across teams.

Assist in translating business cases into technical solutions utilizing various technologies. Support data warehouse design, address performance issues, and contribute to data management standards.

The role requires designing and developing data infrastructure, utilizing Hadoop and Spark in large-scale environments, while also leveraging containerization and automation tools.

The Associate Data Engineer will contribute to Machine Learning and NLP projects, collaborate with cross-functional teams, and enhance threat detection through data-driven intel.

Design and optimize big data solutions using Spark, Scala, ElasticSearch, and more. Collaborate on data engineering, implement CI/CD, and ensure data quality.

The Quantexa Data Engineer will design and optimize big data solutions, build data processing pipelines, and integrate Elasticsearch with Spark, collaborating with teams to ensure data quality and governance.

Data Engineers will design, build, and optimize data pipelines and frameworks for Data Warehouse and Data Lakehouse solutions, ensuring quality and efficiency while adhering to compliance standards.

Design and develop scalable data pipelines, build ingestion frameworks, create APIs, and operationalize ML models while ensuring security.