What you'll be doing

• Building the governance, assurance, and data foundations for consistent, explainable, auditable, and continuously monitored risk decisions.
• Focusing on data governance, control assurance, auditability & explainability, and scalable solutions.
• Building data ownership, lineage, and quality monitoring systems.
• Designing continuous monitoring and validation systems for control performance.
• Implementing audit trails, change history tracking, and explainability tooling for regulatory evidence.
• Designing robust, high-throughput solutions to handle large data volumes across multiple risk domains.
• Building assurance and governance foundations answering key control questions about risk decisions and effectiveness.
• Implementing data quality monitoring, data contracts, and lineage tracking for full traceability.
• Designing automated systems to continuously validate control effectiveness and detect issues proactively.
• Creating audit infrastructure and explainability tools for compliance and regulatory reporting.
• Integrating governance and assurance capabilities into the Risk API platform with clean integration points and shared data contracts.

Requirements

• Strong backend engineering experience building high-throughput, data-intensive systems.
• Hands-on expertise with Kafka, SQL and NoSQL databases.
• Experience designing systems for scale and reliability.
• Data engineering aptitude including data quality frameworks, pipeline orchestration, or lineage tracking.
• Ability to reason about complex distributed systems and design robust, operationally simple solutions.
• Comfortable with ownership and autonomy, defining work from high-level objectives and driving delivery independently.
• Collaborative mindset working across teams including Risk API, Product, and Financial Crime stakeholders to align contracts, data models, and integration patterns.