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Hands-on role managing data platform operations and designing metadata-driven ELT/ETL frameworks (ingestion, orchestration, quality, monitoring) at NUS. Involves data lakes, data warehouses, and tools like Apache Spark, Iceberg, Trino, Python, and proprietary platforms.
Lead Data Engineer designing and building scalable data platforms and pipelines in Singapore, combining hands-on engineering with technical leadership, mentoring, and architecture decisions while collaborating with analytics, software, and AI/ML teams.
Design and lead cloud-native data platform and Data Lakehouse initiatives for a government housing agency, building scalable data architectures, ETL/ELT pipelines, and multi-cloud migration strategies.
The Lead Data Engineer builds and maintains custom data ingestion and MLOps platforms using distributed systems, Apache Airflow, Kafka, Spark, and Databricks. The role involves designing scalable data pipelines and supporting data scientists in deploying ML models on cloud and on-premises infrastructure.
The Data Engineer will design, develop, and maintain scalable data pipelines using Databricks and cloud platforms to support analytics and machine learning. The role focuses on implementing ETL processes, streaming and batch data integration, and ensuring data quality and reliability.
The Senior Data Engineer will design and manage end-to-end data pipelines for a government-focused platform. The role involves building scalable backends and collaborating on data architecture and governance within a hybrid work environment.
The Data Engineer will design, build, and maintain reliable data ingestion and transformation pipelines using AWS and Databricks. The role involves developing data processing layers, ensuring data quality, and collaborating with cross-functional teams to deliver production-ready data solutions.
The Senior Data Engineer will design and maintain scalable cloud-native data pipelines and Data Lakehouse architectures to support evidence-based decision-making. The role involves leveraging modern data engineering tools like Python, SQL, Spark, and Kafka while implementing infrastructure as code and MLOps practices.
This role involves designing and implementing banking data pipelines, processing data from various sources, and writing SQL for reporting. The position requires expertise in Python, Spark, Teradata, and Hadoop within a data engineering context.
The Lead Data Engineer builds and maintains custom data ingestion and MLOps platforms using open-source technologies like Apache Airflow, Kafka, and Spark. The role involves designing scalable data pipelines on Databricks and supporting data scientists in deploying machine learning models at scale.
Design and implement scalable ETL pipelines and data connectors on Azure Databricks, ensuring data quality and smooth deployment using SQL, relational database design, and Delta Lake.
The Lead Data Engineer will design and build scalable data platforms and pipelines to support analytics, digital products, and AI/ML workloads. This hands-on leadership role involves mentoring engineers, establishing engineering standards, and leveraging AI-enabled tools to optimize data workflows.
The Data Engineer will design and optimize big data processing pipelines using Apache Spark, Scala, and Elasticsearch within the Quantexa software ecosystem. The role involves collaborating with cross-functional teams to implement scalable data solutions on OpenShift and supporting compliance-focused financial projects.
The Senior AI Full-Stack Engineer will design and build end-to-end applications using React or Vue for the frontend and REST/GraphQL for the backend. The role involves integrating LLM APIs and architecting data pipelines to support AI-driven features within an R&D environment.
This full-stack role involves developing scalable microservices with Java and Spring Boot alongside responsive front-end interfaces using Angular. The position requires extensive experience with MariaDB, CI/CD pipelines, and containerization tools like Docker and Kubernetes.
The Senior Full-Stack Engineer will develop end-to-end web applications for desktop and cloud platforms using React, HTML5, CSS, Python, and Node.js. The role involves collaborating with designers and AI engineers to build responsive interfaces and robust server-side solutions.
The Principal Geospatial AI Full-Stack Engineer will design and develop geospatial AI-centric digital products and MVPs using ReactJS, NodeJS, Python, and cloud technologies. The role involves collaborating with stakeholders and cross-functional teams to deliver scalable solutions within a government agency.
Senior full-stack engineer designing, developing, and maintaining scalable enterprise applications with React/Angular/Vue.js front-ends and Java/Spring Boot or .NET/C# back-ends, working on APIs, microservices, and CI/CD pipelines.
Senior Full-Stack Developer building scalable RESTful services with Java/Spring Boot and Angular, managing MariaDB databases, and deploying with Docker and Kubernetes via CI/CD pipelines.
Full-stack engineer building RESTful APIs and microservices with Java/Spring Boot on the backend and Angular on the frontend, managing MariaDB databases, and working with Docker/Kubernetes. Weekend and shift work required.
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