SalaryPeak

Lead Data Architect

PURVIEW ASIA PACIFIC PTE. LTD.
Singapore 12+ years Posted Mar 14, 2026

Salary Range

SGD 120,000 - SGD 156,000 /year

SGD 10,000 - SGD 13,000/month

Skills Required

Management SkillsAzureData ModelingArchitectData QualityData EngineeringSQLCompliancePythonTOGAFData ArchitectureMetadataAPIData AnalyticsFinancial Services

Job Description

  • Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related discipline.
  • 12+ years of experience in data architecture and engineering, with at least 5 years in the BFSI domain.
  • Proven track record leading enterprise-scale data modernization programs across multi-cloud environments.
  • Deep expertise in data modeling, governance, lineage, and metadata frameworks.
  • Hands-on experience with real-time, event-driven architectures and AI/ML data enablement.
  • Strong understanding of financial services regulations (MAS TRM, PDPA, BCBS 239).
  • Strong proficiency in Spark, Databricks, Kafka, Flink, or Beam for batch and streaming data processing.
  • Hands-on experience with metadata management and data catalog tools (Collibra, Purview, Apache Atlas).
  • Deep understanding of data quality frameworks and implementation best practices.
  • Strong Knowledge of data security, encryption, and key management techniques.
  • Deep understanding with financial regulations such as MAS TRM, PDPA, Basel III/IV, IFRS 9/17, and BCBS 239.
  • Proficiency in Python, SQL, and API integration.
  • Excellent communication skills and ability to work across data, compliance, and infrastructure teams.
  • Preferred Certifications:
  • Azure Solutions Architect Expert
  • AWS Data Analytics Specialty
  • TOGAF Certified Architect
  • Strong communication and stakeholder management skills across business and technology domains.
  • Deep understanding of financial systems, data flows, and compliance frameworks.
  • Ability to balance strategic architecture vision with hands-on technical leadership.
  • Demonstrated success in mentoring teams and driving data engineering excellence aligned to organizational objectives.