Job Description
Role summary
The Enterprise Database Architect (Fintech) owns the design, modeling, optimization, and governance of Vietpay's core data systems. This role is hands-on and architecture-led. You will build and evolve relational, document, and graph data models, ensure high performance for transaction-heavy fintech workloads, and define standards that help engineering teams ship reliable microservices with clean data contracts. Strong experience in SQL, MongoDB, Neo4j, observability using Grafana, and working closely with middleware and engineering teams is required. Exposure to AI-enabled data workflows is a strong plus and you must be willing to learn new AI tools.
Key responsibilities
1) Database architecture and data modeling
• Own end-to-end data architecture for Vietpay's core platforms: acquiring, settlement, reconciliation, lending, risk, and reporting.
• Design and document relational schemas, MongoDB document models, and Neo4j graph models aligned to business domains.
• Define modeling standards, naming conventions, schema versioning, and change management practices.
• Design data integrity patterns for fintech: ledgers, audit trails, idempotency keys, and reconciliation-friendly structures.
• Partner with product and engineering to translate workflows into clean entities, relationships, and scalable storage patterns.
2) Performance, scalability, and optimization
• Lead performance tuning across query design, indexes, partitioning, caching, and storage strategy.
• Optimize for high-throughput workloads with strict correctness requirements: transaction posting, settlement, and reporting.
• Define scaling approaches such as read replicas, sharding strategies, and workload separation where appropriate.
• Review and improve slow queries and critical paths, establish performance baselines and regression checks.
• Guide teams on efficient data access patterns and cost-aware design to reduce infrastructure spend.
3) Microservices and API-driven data systems
• Architect database patterns that integrate cleanly with microservices and API layers (service-owned data where possible).
• Define data consistency approaches (strong vs eventual), including event-driven propagation, outbox patterns, and retries.
• Establish data contracts and integration guidelines with middleware teams to reduce coupling and failures.
• Design strategies for deduplication, concurrency control, and safe retries across distributed services.
• Support schema evolution across services without breaking production, including backward-compatible migrations.
4) Observability and operations (Grafana)
• Establish database observability standards: metrics, alerts, SLOs, and dashboards.
• Build and maintain Grafana dashboards for latency, throughput, errors, capacity, replication lag, and resource saturation.
• Partner with DevOps/SRE on backups, restore testing, failover, and disaster recovery runbooks.
• Support incident response and post-mortems, drive remediation to prevent repeat database-related issues.
5) Security, governance, and AI readiness
• Implement security best practices: least privilege access, encryption, audit logging, and secure secrets handling.
• Define governance for PII and sensitive financial data: retention, masking/tokenization, and access reviews.
• Ensure architectures support compliance and auditability requirements for financial services.
• Prepare data foundations for analytics and AI, structure datasets and metadata so teams can discover patterns and build models using modern AI tools.
Your Skills and ExperienceMust have
• Must be fluent in English
• 7+ years of experience in enterprise database engineering or architecture roles.
• Strong hands-on expertise in SQL, including data modeling, transactions, indexing, and query optimization.
• Strong hands-on expertise in MongoDB, including document modeling, indexing, and performance tuning; familiarity with replication and sharding concepts.
• Hands-on experience with Neo4j, including graph data modeling and Cypher query design; ability to choose the right graph use cases.
• Proven experience supporting microservices platforms and API-driven architectures, including schema evolution and migration strategy.
• Strong operational mindset: monitoring, backups, restore testing, high availability, and disaster recovery planning.
• Practical experience with observability and dashboards using Grafana (and related metrics/alerting stacks).
• Excellent English communication skills (spoken and written), comfortable working with international teams.
Preferred qualifications
• Experience in fintech, payments, banking, insurance, or other regulated enterprise environments.
• Experience with event-driven architectures and messaging (Kafka, RabbitMQ, or equivalent).
• Exposure to analytics and warehousing patterns (ETL/ELT, dimensional modeling, or data lake concepts).
• Experience designing for auditability and reconciliation processes (ledgers, settlements, chargeback-style workflows).
• Exposure to AI/ML data preparation or using AI tools for schema review, query optimization, and pattern discovery; willingness to learn and adopt new AI workflows.
Tools and working methods
• Databases: PostgreSQL or MySQL, MongoDB, Neo4j; strong SQL-first discipline for transactional data.
• Observability: Grafana (dashboards), plus common metric and alerting stacks as used by DevOps/SRE.
• Data operations: migration and versioning tools (Flyway, Liquibase, or equivalent), backup and restore automation.
• Collaboration: Jira/Confluence/Notion, Git-based workflows, and clear written documentation and decision logs.
Why You'll Love Working Here- International fintech & digital banking firm
- Top salary, bonus & stock options
- Work & travel globally with innovation teams
- Social insurance based on full salary
- Full Training will be provided to Candidate
Benefits
- International fintech & digital banking firm
- Top salary, bonus & stock options
- Work & travel globally with innovation teams
- Social insurance based on full salary
- Full Training will be provided to Candidate