Database Architect

Key Responsibilities

Data Architecture & Platform Design

. Architect and implement Data Lakehouse solutions on cloud platforms (AWS / Azure / GCP).

. Design end-to-end data ecosystems covering ingestion, storage, modelling, analytics, and governance.

. Define data standards, blueprints, and reference architectures across the organisation.

. Ensure scalable, secure, and compliant data environments aligned to banking and AML requirements.

Engineering & Delivery

. Lead ground-up platform builds, taking projects from concept to production.

. Oversee data engineering streams, including pipelines, orchestration, quality, lineage, and metadata.

. Support integration of AI/ML tools into the data platform.

. Work across multiple project streams and client groups within a broader program.

Analytics & Consumption Layer

. Partner with analytics ensure data models support Business Intelligence, reporting, AML monitoring, and regulatory use cases.

. Understand end-to-end flows from source systems - data lake-house - analytics.

Data Governance & Operating Model

. Implement and maintain data governance frameworks, including stewardship, lineage, and quality controls.

. Support ongoing client environment maintenance, architecture enhancements, and governance compliance.

Stakeholder Management

. Communicate effectively with business, technology, and regional leadership.

. Translate complex architecture into clear business outcomes.

. Influence decision-making across cross-functional teams.

Regional Scope

. Work across multiple APAC markets including Thailand, Korea, Japan, Myanmar, India, and the Philippines.

. Understand regional variations in data, regulation, and infrastructure.

. Travel required once per quarter or less.

Broader Architecture & Integration

. Contribute beyond data architecture into software, cloud architecture, integration patterns, and enterprise services.

. Support the setup and operation of cloud environments.

Ideal Candidate Profile:

. 15+ years in data architecture, data engineering, or enterprise data roles.

. Strong exposure to Banking and Financial Services industries

. Ideally some experience with the Corporate Banking and AML / Financial Crime data domains.

. Proven track record delivering large-scale, multi-stream data programs.

. Experience working in regional APAC environments.

Technical Skills

. Data Lakehouse architectures (Delta Lake, Iceberg, Hudi).

. Cloud platforms: AWS, Azure, or GCP.

. Data modelling (conceptual, logical, physical).

. ETL/ELT tools, orchestration frameworks, streaming technologies.

. Data governance, metadata management, lineage tools.

. Understanding of AI/ML data integration.

. Comfortable with broader enterprise software, API integration and enterprise architecture concepts.

. Comfortable with some AI tooling.

Soft Skills:

. Strong communication and stakeholder engagement.

. Ability to operate in complex, multi-country environments.

. Comfortable leading both engineering-heavy and governance-heavy workstreams.