Top Data Engineer Jobs in Singapore

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

The Data Engineer is responsible for designing and maintaining scalable data systems, building data pipelines, and collaborating with teams to support analytics and AI use cases.

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

The role involves designing data architecture, building ETL/ELT workflows, ensuring data quality, providing technical leadership, and collaborating with cross-functional teams to create scalable data systems for AI projects.

Join Razer as a Data Engineer to build data infrastructure for AI and machine learning, focusing on optimization, data pipelines, and collaboration with teams for AI-driven initiatives.

The Data Engineer will manage the end-to-end data lifecycle, collaborating with quantitative researchers to support investment strategies and ensure data quality and readiness.

The Platforms and Data Engineer will develop and manage high-performance analytics solutions, design data transformation processes, maintain data systems, and support AI projects.

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.

The Cloudera Data Engineer is responsible for building and managing data pipelines and platforms, focusing on the Cloudera Hadoop ecosystem while collaborating with data teams.

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.

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

As a Data Engineer, you will build data pipelines using AWS, support AI/ML projects, improve existing systems, and ensure security compliance.

Maintain and improve data pipelines and invoicing-related data quality checks; build visualizations; collaborate with data engineers and stakeholders to evolve the Snowflake/dbt/Dagster tech stack supporting accurate, timely invoicing.

Design and deploy scalable batch and streaming data pipelines, semantic/ dimensional models, and BI solutions for Finance. Operationalize production GenAI (RAG, prompt engineering, vectorization), implement CI/CD and observability, ensure SOX/PII controls, and enable analytics through dashboards and documentation.

The AWS AI & Data Origination Lead drives growth by identifying client challenges and developing AI and cloud solutions while leading negotiations for business value.

The Pre-Sales Engineer for AI & Data designs solutions for clients, leads pre-sales processes, collaborates with teams, and communicates technical value to stakeholders.

The Senior Data Engineer will design and optimize data pipelines and models using Databricks, PySpark, and cloud platforms, leveraging deep data engineering expertise to enhance data processing and ensure quality delivery.

The Data Centre Engineer will manage data and colocation centres, coordinate logistics, and ensure operational standards for security and upkeep.

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.

Design, build, and optimize data pipelines and DBT projects. Collaborate with teams to improve data-driven decision-making and advocate automation.

Design, develop, and maintain data pipelines, optimize SQL queries, and ensure data quality while collaborating with stakeholders in the banking sector.

The Senior Data Engineer designs and builds data pipelines on cloud platforms, implements data lakehouse solutions, and collaborates with teams while ensuring data governance and quality checks.

The R&D Data Science Engineer designs and optimizes data systems, develops algorithms, and collaborates on digital health technology projects to improve drug development processes.

As a Software Engineer for Data Orchestration, you'll develop systems for high volume data processing, focusing on real-time fraud monitoring tools with a DevOps approach and collaborative workflows.