What you'll be doing

• Build the governance, assurance, and data foundations for consistent, explainable, auditable, and continuously monitored risk decisions.
• Create data governance systems for data ownership, lineage, and quality monitoring to ensure trusted data for risk decisions.
• Design continuous monitoring and validation systems for control assurance including trigger validation, drift detection, coverage analysis, and control health scoring.
• Implement auditability and explainability tooling with end-to-end audit trails and change history tracking for regulatory evidence generation.
• Develop scalable, high-throughput solutions adaptable across multiple risk domains.
• Build data quality monitoring, data contracts, and lineage tracking for full traceability from risk decisions to source data.
• Design automated monitoring systems that validate control effectiveness and detect drift, false positives/negatives, and coverage gaps.
• Create audit trail infrastructure and explainability tooling to ease regulatory reporting and compliance evidence generation.
• Collaborate with the Risk API team to embed governance and assurance capabilities into the core platform with clean integration points and shared data contracts.

Requirements

• Proven experience building high-throughput, data-intensive backend systems with hands-on expertise in Kafka, SQL, NoSQL databases, and scalable, reliable design.
• Experience with data quality frameworks, pipeline orchestration, or lineage tracking to ensure trustworthy data at scale.
• Strong systems thinking skills to reason about complex distributed systems, identify failure modes, and design robust, operationally simple solutions.
• Ability to work autonomously with ownership, handle ambiguity, set own work from high-level objectives, and deliver end-to-end.
• Collaborative mindset to work effectively across teams including Risk API, Product, and FinCrime stakeholders to align on data models, contracts, and integration patterns.