Top Data Engineer Jobs in Singapore
The Data Engineer will manage patent data operations, design data processing solutions, monitor data quality, optimize systems, and collaborate with data architects to enhance scalability and stability.
As a Data Engineer at OKX, you'll design and build resilient data pipelines for batch and real-time data, architect cloud data infrastructure, collaborate with teams to develop data-driven platforms, ensure data integrity, and improve data standards and monitoring.
The Data Engineer will be responsible for collecting, designing, and processing payments data, unifying and standardizing it to create comprehensive digital assets. The role involves developing evaluation metrics, enhancing data quality, creating data-driven tools, and maintaining data integrity to facilitate effective access to data.
As a Senior Staff/Principal Data Engineer, you will design and maintain real-time and batch data processing pipelines using Flink, focusing on architecture and scalability. Collaborating with data scientists and cross-functional teams, you will address performance challenges and improve data integrity, particularly in FinTech or blockchain contexts.
Seeking a highly skilled Big Data Engineer with 4 years of experience in managing data engineering jobs in a big data environment. Responsible for designing, developing, and maintaining data ingestion and processing jobs as per business requirements.
Work as an Analyst Programmer/Data Engineer in a dynamic and empowering environment. Collaborate with experts in the field to make a difference in the lives of clients worldwide.
The Data Engineer role involves building optimal ETL processes, managing data pipelines, and designing scalable data platforms for analytics. Responsibilities include improving data governance, collaborating with business teams, and implementing DevOps for data projects.
The Data Engineer will analyze data needs, migrate data collection methods, design and implement data jobs, develop test plans, support production issues, and collaborate on DevOps deployments. Proficiency in data visualization tools and big data technologies is required.
The Data Engineer will assist in developing and optimizing ETL processes using PySpark and Databricks while collaborating on data models in AWS. Responsibilities include maintaining data pipelines, utilizing version control with GitHub, and implementing CI/CD practices. The role also involves documenting workflows and supporting best coding practices.
Design and maintain scalable data pipelines using Hadoop and Spark, writing optimized jobs in Scala and utilizing SQL for data management. Collaborate with data scientists, monitor workflows, implement data governance practices, and document processes while staying updated with industry trends.
The Data Engineer II role at Cencora focuses on providing accurate data support for Legal and Compliance departments. Responsibilities include data extraction and analysis, data quality validation, and developing analytics models to address business challenges. The position requires data monitoring, collaborating with teams, and ensuring data integrity for effective decision-making.
Collaborate with analysis and development teams on data modelling activities, contribute to data application projects, possess expertise in data warehousing and big data technologies, and demonstrate strong communication skills.
The Data Engineer is responsible for building and optimizing big data pipelines, performing root cause analysis, supporting data modeling and implementation activities, and processing large unstructured datasets. The role includes CI/CD activities and working with various cloud platforms.
The Data Engineer will design, develop, and implement Spark Scala applications and data processing pipelines, integrating Elasticsearch for data indexing and retrieval. Responsibilities include optimizing Spark jobs for performance, collaborating with stakeholders, implementing data transformations, and resolving performance issues.
As a Data Engineer, you will design, implement, and optimize data pipelines and workflows, ensuring scalable and reliable data infrastructure. Responsibilities include developing ETL processes, monitoring data quality, optimizing performance, and collaborating with stakeholders for data requirements.
As a Data Engineer, you will design and maintain efficient data pipelines, ensuring the availability and reliability of ML Solutions using technologies such as Hadoop and Spark. Responsibilities include data transformation, collaboration with teams, ensuring data quality, and implementing governance practices. You will also optimize workflows for containerized deployments and streamline processes with DevOps teams.
The Data Engineer II will enhance existing business analytics solutions, perform data mining to support sales and market growth, ensure data quality and integrity, analyze datasets for trends, and collaborate across teams for performance forecasting and reporting.
The Data Engineer will design and maintain SQL data warehouses, optimize stored procedures, build reports using SSRS, create dashboards with Superset, and develop data pipelines with Airflow for integration and automation. Requires 3+ years of experience and expertise in relevant technologies.
Leverage advanced statistical and computational methodologies to deliver insights and strategic opportunities for improving healthcare quality, patient experience, and cost. Integrate, analyze, and interpret business level data from multiple sources. Develop scalable processes for large-scale data analyses and model development. Manipulate and refine large datasets, monitor complex systems, and provide support on data-related solutions to business partners and clients.
As a Data Engineer, you will design and implement data solutions focusing on developing ETL processes, conducting data mapping, optimizing performance, and ensuring data quality. Your role involves collaboration with stakeholders and documenting processes for future reference.
The Data Engineer will design, implement, and maintain ETL processes, manage data mapping documentation, collaborate with stakeholders to meet data requirements, conduct data quality checks, optimize workflows, and troubleshoot issues. They will also stay updated on best practices in data engineering.
As a Data Engineer, you will design and optimize big data solutions using Apache Spark, Scala, and Elasticsearch. Responsibilities include developing data processing pipelines, integrating Elasticsearch, troubleshooting issues, and ensuring data quality. You will also collaborate with DevOps teams and implement CI/CD pipelines on OpenShift.
The Data Engineer will design, develop, and implement Spark Scala applications and data processing pipelines for structured and unstructured data. They will integrate Elasticsearch for efficient data handling, optimize Spark jobs for performance, and collaborate with teams to translate requirements into solutions while maintaining data quality and addressing performance issues.
The Sr Cloud Data Engineer will lead data integration efforts, create and maintain data management standards, develop data pipelines using AWS services, manage complex data models, and present data insights to both technical and non-technical stakeholders. They will ensure data quality and facilitate collaboration among various departments.
The Lead Data Engineer will oversee the development of data warehouse systems, guide engineering teams on ETL jobs and data modeling, collaborate with cross-functional stakeholders to define specifications, and ensure best practices in data management and documentation.
All Filters
No Results
No Results