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Responsibilities Pre-Sales Solution Support: Partner with KAMs to define strategic customer technical needs; deliver customized data center solutions (magnetic bearing chillers, fan wall, liquid CDU, building controls,…
A GenAI engineer at EtonHouse builds AI features and dashboards for school operations, working with Azure OpenAI, SQL, Python, and BI tools. Day to day they create ETL pipelines, integrate APIs, monitor solutions with Application Insights, and collaborate with teachers and IT teams.
Supports end-to-end server infrastructure projects in data centers, handling deployment, racking, cabling, and configuration while coordinating with engineers, project managers, and service partners. Core technologies include server hardware, Linux/Windows Server, VMware, and networking.
Implements and maintains the company's backbone data center infrastructure — installing and troubleshooting server and network hardware, deploying Linux servers, managing assets and documentation, and coordinating with facility partners on cooling, UPS and fire suppression — to keep products running across all regions.
Lead data-driven traffic innovation at Singapore's Land Transport Authority: run analytics and ops-tech projects, build user-friendly dashboards, and work with cross-functional teams to turn complex transport data into strategies that improve the road network's reliability, performance and sustainability.
A data engineering internship at Sembcorp in Singapore, working with data science and architecture teams to build and maintain production data pipelines, ML retraining/monitoring frameworks, and AI-assistant data products for the renewables and utilities space, using Python, SQL, and big data/cloud tools like Spark.
A data engineer in NUHS's Central Data Engineering Office who builds and maintains cloud-based data pipelines and ETL processes using Databricks and AWS, ensuring data scalability, quality, and availability for analytics and AI. Requires SQL, a programming language like Python, and collaboration with data scientists and business stakeholders.
Leads a data engineering team that designs, builds, and optimizes data warehouse infrastructure and ETL/ELT pipelines on Alibaba Cloud (MaxCompute, Hologres, PAI, DataWorks), while enforcing data quality, governance, and security and partnering with analytics and business teams.
Internship in Singapore supporting Sembcorp's data engineering and AI initiatives: maintaining scalable batch and real-time streaming data pipelines, integrating data from APIs, IoT sensors and streaming platforms, and building ML pipeline components on Azure cloud for renewable analytics and AI-assistant data platforms.
A data/AI engineer role at EtonHouse in Singapore: build Generative AI features using Azure OpenAI and RAG, work with project data in Python and SQL, and build simple ETL pipelines. Also creates Power BI dashboards, deploys with Docker/Terraform, does API integrations, and tests output quality with a focus on privacy compliance.
Vistra is hiring a Machine Learning Data Engineer in Singapore to design, fine-tune, and deploy ML models and AI-driven document-processing data pipelines on AWS Bedrock for corporate secretarial and accounting use cases. The role spans end-to-end MLOps, requiring ~5-7 years of AI/data engineering experience, Python/Node.js, ETL expertise, and strong mathematical foundations in model training.
Data Engineer / Assistant Manager at synapxe (Singapore's national HealthTech agency) shaping and running the TRUST national healthcare data platform: translating analytics needs into data strategy, overseeing anonymised dataset provisioning, and implementing common data models and quality programmes. Core tech: ETL, cloud (AWS), SQL/NoSQL, big data, and healthcare data modelling (e.g. OMOP CDM).
An algorithm data engineer at Shopee building feature platforms/feature stores, high-quality offline and real-time datasets, and experimentation pipelines that power e-commerce algorithm teams. Core work spans big data processing with Spark, Flink, Kafka, ClickHouse and programming in Python, Java, Scala, or SQL.
AI Data Engineer in Singapore designing and owning end-to-end AI-driven data pipelines on AWS (Bedrock) for corporate secretarial and accounting document processing. Day to day: fine-tuning and deploying ML models, building multimodal pipelines, and applying MLOps practices with Python, ETL/ELT, and AWS services.
NTT Data Asia Pacific is hiring Data Engineers (Junior, Senior, and Lead) in Singapore on a 1-year renewable contract. The role focuses on designing and optimizing ETL/data pipelines using Informatica/IDMC and Databricks with Python, plus AWS Cloud and Tableau/OAS for visualization and reporting.
Designs, builds, and optimizes scalable ETL/ELT data pipelines, data models, and data warehouses using Python, PySpark, and SQL, while tuning Spark jobs, integrating data from APIs, databases, and cloud storage, and ensuring data quality, governance, and performance.
Data engineer on Shopee's Marketplace App & Mobile team, building and optimizing the mobile data warehouse with real-time and offline ingestion, modeling, and governance. Works with Spark/Flink/Kafka/ClickHouse-style big data tools and Java/Scala/Python/SQL to power app analytics, A/B testing, and user behavior tracking.
Builds and maintains real-time and batch data pipelines processing 1.6-2 billion clickstream events per month for SPH Media's digital platforms, powering audience insights for product and business teams. Core stack: Apache Flink, Kafka, Iceberg/Paimon, and AWS (S3, Athena, EventBridge, Lambda).
Data Engineer building the compliance 'trust layer' of a fast-growing AI company's data infrastructure in Singapore: designing data masking/anonymization pipelines, profiling and classifying sensitive datasets, and translating regulations (GDPR, PDPA, SOC2) into technical controls using SQL, Python, Spark, Airflow, Kafka, and Hive.
Freelance data engineer who designs, builds, and maintains ELT pipelines in a cloud environment using Snowflake, Airflow, PySpark, AWS, Fivetran, and dbt. Day to day involves monitoring data quality and reliability, supporting legacy-to-cloud migration, and collaborating with BI and architecture teams.
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