Director of Data

About MetaComp

MetaComp Pte Ltd is a prominent digital payment solutions provider based in Singapore, authorized and regulated by the Monetary Authority of Singapore as a Major Payment Institution. It offers Digital Payment Token Services and Cross-border Payment Transfers. Operating under a platform-to-business-to-client model, MetaComp supplies clients with an integrated end-to-end service suite to enable safe, secure, and compliant entry into the digital asset space. Together with its parent company, Metaverse Green Exchange Pte. Ltd., MetaComp delivers its services through the Client Assets Management Platform (CAMP), facilitating business growth in digital asset offerings such as OTC transactions, fiat payments, digital custody, and prime brokerage.

Role Overview

We seek a Director of Data to spearhead the organization's data strategy, governance, analytics, database management, data platform development, and AI integration efforts. The role involves creating a secure, reliable, and AI-capable data infrastructure to support key applications, business insights, regulatory compliance, product innovation, and enterprise AI initiatives. The ideal candidate will be an active leader linking data architecture and governance to impactful business outcomes.

Key Responsibilities

• Develop and implement a company-wide data and AI strategy, including architecture, governance models, and roadmaps.
• Define ownership across database management, data engineering, analytics, business intelligence, governance, and AI data products.
• Build and manage a multidisciplinary high-performance data team.
• Collaborate with Product, Engineering, AI, Operations, Compliance, Security, and Infrastructure departments.
• Allocate data investments based on business value, compliance, operational risk, and AI preparedness.
• Oversee architecture, security, lifecycle, and reliability of production databases.
• Set standards for database design, schema management, performance tuning, capacity planning, upgrades, patching, and change control.
• Ensure databases meet required availability, performance, backup, recovery, RTO, and RPO objectives.
• Implement monitoring, replication, high availability, disaster recovery, and operational procedures.
• Regularly test restoration, failover, and resilience with documentation.
• Manage database access controls, encryption, audit logging, data masking, and segregation of duties.
• Optimize database performance and costs while maintaining security and reliability.
• Lead cloud-based data platform development encompassing data warehouses, lakehouses, ETL/ELT, streaming, orchestration, and data serving.
• Integrate structured and unstructured data from diverse sources with guaranteed quality, performance, and security.
• Define standards for data modeling, integration, testing, metadata, lineage, documentation, and lifecycle processes.
• Create reusable, governed data products consumable by applications, analytics, AI models, and agents.
• Build a reliable data foundation for generative AI, machine learning, predictive analytics, and enterprise AI agents.
• Develop governed pipelines for AI data preparation including enrichment, labeling, indexing, and serving.
• Facilitate technologies like retrieval-augmented generation, vector databases, semantic search, embeddings, feature stores, knowledge graphs, and real-time AI data services.
• Maintain data-quality and freshness standards for AI while safeguarding sensitive and restricted data.
• Implement governance for AI datasets addressing provenance, consent, access, retention, IP, and usage policies.
• Work with AI teams to assess model inputs, retrieval quality, traceability, and output reliability.
• Monitor AI data pipelines for knowledge freshness, data drift, retrieval accuracy, and usage.
• Apply AI to enhance data operations like discovery, classification, quality management, reconciliation, anomaly detection, metadata creation, and automation.
• Measure AI-enabled data product effectiveness regarding business impact, adoption, quality, risk, and cost.
• Implement enterprise governance covering data ownership, classification, quality, lineage, retention, access, and usage.
• Ensure controls for personal, financial, transactional, confidential, and regulated data are effective.
• Maintain searchable data catalogs, glossaries, lineage, and ownership models for critical data assets.
• Define and oversee data-quality standards, ensuring issues are addressed within set SLAs.
• Comply with privacy, security, regulatory, and audit standards with maintained evidence for reviews and audits.
• Establish enterprise BI frameworks with trusted metrics, standardized definitions, and governed data models.
• Deliver timely operational, financial, customer, risk, and management insights via dashboards, self-service analytics, and natural-language queries.
• Support AI-assisted analysis with accuracy, explainability, controlled access, and human oversight.
• Reduce manual reporting and reconciliation through standardized data products and intelligent automation.
• Translate business challenges into actionable forecasts and insights.

Qualifications

• Over 5 years' experience in database management, data engineering, platforms, analytics, or AI data roles with significant leadership background.
• Demonstrated success defining and implementing enterprise data strategies and modern cloud data platforms.
• Extensive experience managing critical production databases in high-availability environments.
• Strong familiarity with relational and NoSQL databases, data architecture, modeling, performance optimization, replication, backup, and disaster recovery.
• Proficiency with data warehousing, lakehouses, ETL/ELT, APIs, event streaming, and real-time processing.
• Practical understanding of generative AI, machine learning, retrieval-augmented generation, embeddings, vector search, knowledge management, and AI data workflows.
• Expertise in preparing and governing enterprise data for AI and advanced analytics applications.
• Deep knowledge of data governance, quality frameworks, metadata management, security, privacy, retention, and regulatory compliance.
• Capable of delivering enterprise business intelligence, management reporting, and self-service analytics solutions.
• Adept at leading cross-functional initiatives and influencing senior stakeholders in business and technology.
• Strong business acumen, structured thinking, communication, and execution capabilities.

Preferred Experience

• Background in fintech, payments, banking, digital assets, or regulated industries.
• Experience handling high-volume transactional and financial datasets.
• Technical familiarity with AWS, PostgreSQL, MySQL, Oracle, RDS/Aurora, DynamoDB, Redis, Snowflake, Databricks, dbt, Airflow, Kafka, and Spark.
• Knowledge of AI/data technologies including vector databases, knowledge graphs, model gateways, LLM platforms, MLflow, feature stores, and AI evaluation frameworks.
• Experience delivering data products for AI agents, intelligent automation, fraud detection, risk management, or customer analytics.
• Understanding of responsible AI, model risk, data privacy, cloud security, and operational resilience.

Success Indicators

• Consistent achievement of critical database availability, performance, security, backup, and recovery targets.
• A scalable, production-grade, AI-ready enterprise data platform is established.
• Clear data ownership, definitions, lineage, quality controls, and access policies are in place for critical data.
• AI applications and agents utilize trusted, governed, traceable, and current enterprise data.
• Business reporting and AI-based insights are prompt, accurate, consistent, and actionable.
• Manual reporting, reconciliation, and data management efforts are significantly reduced.
• Data and AI capabilities provide demonstrable enhancements in decision-making, customer experience, operational efficiency, risk management, and compliance.

Diversity and Inclusion

We foster a workplace culture that values respect, inclusion, and empowerment for all individuals, celebrating diverse backgrounds, ethnicities, genders, identities, orientations, experiences, and perspectives. We proudly uphold equal opportunity employment policies without discrimination based on protected characteristics.