Lead Data Solution Architect, Risk & Financial Crime

Randstad NV; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Randstad NV seeks a senior Data Platform Architect to design and deliver scalable analytics solutions across the software lifecycle. You will translate business and regulatory requirements into robust architectural designs and lead end-to-end delivery for enterprise data platforms.

You will evaluate new tooling, collaborate on PoCs, and partner with cross-functional teams to ensure data quality and operational excellence in a modern data landscape.

Qualifications

• 8+ years leading end-to-end delivery of enterprise data and analytics solutions.
• Two relevant technical certifications across data platforms, cloud, or analytics technologies.

Responsibilities

• Drive end-to-end solution delivery for large-scale analytics platforms, translating complex business and regulatory needs into robust architectural designs.
• Review, refine, and approve testing strategies, validation controls, and reconciliation frameworks to protect platform integrity.
• Evaluate emerging data and analytics tooling, collaborating on proof-of-concept initiatives to advance enterprise modernization.
• Formulate technical architectures supporting NLP, entity resolution, and network analytics.
• Partner cross-functionally to resolve incidents, perform root cause analysis, and reinforce data quality controls.

Skills

end-to-end data architectures

open table formats

distributed processing engines

Apache Iceberg

Spark

Python

Informatica PowerCenter

Cloudera Hadoop

Data modelling

Education

Bachelor Degree

Tools

Informatica PowerCenter

Big Data Management

Job description

Randstad NV seeks a senior Data Platform Architect to design and deliver scalable analytics solutions across the software lifecycle. You will translate business and regulatory requirements into robust architectural designs and lead end-to-end delivery for enterprise data platforms.

You will evaluate new tooling, collaborate on PoCs, and partner with cross-functional teams to ensure data quality and operational excellence in a modern data landscape.