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Builds the data foundations for Temasek's agentic AI systems: agent-ready data architectures, RAG pipelines, vector/graph knowledge bases, and data quality, lineage, and observability frameworks over structured and unstructured investment data. Core stack includes Python, dbt, Airflow/Spark, streaming tools, and vector databases.
Senior AI Data Engineer at Temasek who designs and builds AI-ready data architectures — data pipelines, RAG workflows, and knowledge graphs — so AI systems can reliably reason over structured and unstructured investment data. The role also covers data quality, lineage, and governance across global domains while meeting regulatory requirements.
A data engineering internship at Temasek's Singapore office, supporting data pipelines, data quality, and AI-ready data preparation for AI applications. Day-to-day involves cloud and big data technologies (AWS, Spark, Airflow), SQL, and dashboarding with tools like Tableau alongside data engineers, AI engineers, and business stakeholders.
Design and evolve an enterprise data platform for AI applications, focusing on RAG pipelines, vector databases, and governance standards.
Design and maintain AI-ready data architectures, including vector and graph databases, to power retrieval-augmented generation systems and enterprise analytics for investment and market intelligence.
Leads SAP SuccessFactors and HR tech initiatives, managing implementations, integrations, and vendor coordination to optimize HR processes and ensure compliance and reliability.
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