What you'll be doing

• Build governance, assurance, and data foundations to ensure consistent, explainable, auditable, and continuously monitored risk decisions.
• Focus on data governance by building and maintaining data ownership, lineage, and quality monitoring systems.
• Design continuous monitoring and validation systems for control assurance, including trigger validation, drift detection, coverage analysis, and control health scoring.
• Implement audit trails, change history tracking, and explainability tooling for regulatory evidence generation.
• Design scalable, high-throughput solutions across multiple risk domains.
• Build assurance and governance foundations answering key control questions about triggers, data availability, decision correctness, and control effectiveness.
• Implement data quality monitoring, data contracts, and lineage tracking for full traceability.
• Design automated monitoring systems to continuously validate control effectiveness and detect issues proactively.
• Create infrastructure for audit trails and explainability to streamline regulatory reporting and compliance.
• Collaborate closely with the Risk API team to integrate governance and assurance capabilities, ensuring clean integration and shared data contracts.

Requirements

• Proven experience in backend engineering building high-throughput, data-intensive systems using technologies like Kafka, SQL, and NoSQL databases.
• Experience with data quality frameworks, pipeline orchestration, or data lineage tracking to ensure trustworthy data at scale.
• Strong systems thinking skills to reason about complex distributed systems and design robust, operationally simple solutions.
• Ability to operate with ownership and autonomy, managing ambiguity and delivering end-to-end without close supervision.
• Collaborative mindset to work effectively across teams, especially with Risk API, Product, and Financial Crime stakeholders to align on contracts and integration.