- Singapore
全职 Principal Consultant 工作, 薪水 up to SGD 14,000, IMPACT AI TECHNOLOGIES PTE. LTD. 公司招聘中 - Ricebowl
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工作地点
职位描述
岗位职责
Requirements
Bachelor’s or master’s degree in Computer Science, Engineering, Data Management or a related discipline.
At least 10 years of relevant experience, including architecture leadership for large enterprise or banking data programmes.
Strong ownership, analytical thinking and disciplined delivery in a regulated environment.
Clear communication and effective collaboration across business, architecture, engineering, testing and operations teams
Key Domain/ Technical Skills:
FUNCTIONAL / DOMAIN
Enterprise data architecture for banking, including customer, payments, risk, finance and regulatory data.
Data governance, BCBS 239 principles, metadata, lineage, controls, auditability and regulatory traceability.
Architecture governance, design assurance and transition planning across multiple workstreams.
TECHNICAL
Teradata, Hadoop/Cloudera, Qlik Sense, Power BI, Snowflake, Databricks and enterprise data platforms.
Lakehouse, Data Mesh, Data Fabric, data products, semantic layers, APIs, streaming and event-driven integration.
Cloud data services, Kubernetes, security architecture, DevOps and enterprise integration patterns.
Bachelor’s or master’s degree in Computer Science, Engineering, Data Management or a related discipline.
At least 10 years of relevant experience, including architecture leadership for large enterprise or banking data programmes.
Strong ownership, analytical thinking and disciplined delivery in a regulated environment.
Clear communication and effective collaboration across business, architecture, engineering, testing and operations teams
Key Domain/ Technical Skills:
FUNCTIONAL / DOMAIN
Enterprise data architecture for banking, including customer, payments, risk, finance and regulatory data.
Data governance, BCBS 239 principles, metadata, lineage, controls, auditability and regulatory traceability.
Architecture governance, design assurance and transition planning across multiple workstreams.
TECHNICAL
Teradata, Hadoop/Cloudera, Qlik Sense, Power BI, Snowflake, Databricks and enterprise data platforms.
Lakehouse, Data Mesh, Data Fabric, data products, semantic layers, APIs, streaming and event-driven integration.
Cloud data services, Kubernetes, security architecture, DevOps and enterprise integration patterns.
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