Top Data Engineer Jobs in Singapore

The Data Engineer (Python) will be responsible for ingesting data from various sources, curating data assets, collaborating with teams, deploying ML models, and architecting data pipelines to enable informed decision-making. The role focuses on enhancing the user experience through data-driven solutions.

The Data Engineer will analyze data needs, document requirements, and implement efficient data collection mechanisms. This role includes planning and designing data engineering jobs, developing test plans, and automating processes to enhance efficiency. They will also support deployment of new solutions and ensure smooth operations of IT services, addressing production issues as needed.

As a Junior Data Engineer, you will support the Regional Data team by building data pipelines, ingesting data sources into the data warehouse, and creating tools for data consumers. You will ensure high-quality data assets for data scientists and collaborate with cross-functional teams to enhance data-driven decision-making.

As a Cloud Data Engineer at Kyndryl, you will bridge business challenges with innovative data solutions, utilizing statistical modeling and data preparation techniques. You'll deploy models, ensure data security, and lead AI and Generative AI projects while collaborating with customers to assess their data maturity. Responsibilities include developing end-to-end AI proof of concept projects and enhancing data and AI product deployments.

As a Junior Data Engineer, you will design, develop, and maintain data pipelines using Hadoop and Spark. You will collaborate with teams to ensure data quality, and implement CI/CD processes with DevOps. The role requires optimizing workflows for containerized deployment and mentoring junior members.

As a Senior Data Engineer at Walmart, you will develop scalable solutions for extracting, transforming, and loading big data, ensuring data quality and governance, and collaborating with engineering teams globally to optimize data workflows.

The Data Engineer will develop and optimize ETL processes using PySpark and Databricks, design and implement data models in AWS, monitor data pipelines for quality, utilize GitHub for version control, and contribute to CI/CD practices and documentation.

The Data Engineer will design, develop, and maintain scalable data pipelines and ETL processes using Hadoop and Spark, write optimized data processing jobs in Scala, and utilize SQL for data querying. Collaboration with data scientists is essential to deliver solutions that meet business needs, monitor workflows for performance, and document processes for knowledge sharing.