Requirements

• Strong Backend Engineering: Proven experience building high-throughput, data-intensive systems in any language. Hands-on expertise with Kafka, SQL and NoSQL databases, and designing for scale and reliability.
• Data Engineering Aptitude: Experience with data quality frameworks, pipeline orchestration, or lineage tracking. Understanding of making data trustworthy at scale.
• Systems Thinking: Ability to reason about complex distributed systems, identify failure modes, and design robust and operationally simple solutions.
• Ownership & Autonomy: Comfortable operating with ambiguity, defining your own work from high-level objectives, and driving delivery end-to-end without close direction.
• Collaborative Mindset: Ability to work effectively across team boundaries, particularly with Risk API, Product, and FinCrime stakeholders to align on contracts, data models, and integration patterns.

What you'll be doing

• Build Data Trust: Implement data quality monitoring, data contracts, and lineage tracking to ensure traceability from risk decisions back to source data.
• Deliver Continuous Assurance: Design and build automated monitoring systems to continuously validate control effectiveness, detecting drift, false positives/negatives, and coverage gaps early.
• Enable Auditability: Create audit trail infrastructure and explainability tooling that reduces effort for regulatory reporting and compliance evidence generation.
• Integrate with Risk API: Collaborate closely with the Risk API team to embed governance and assurance capabilities into the core platform with clean integration points and shared data contracts.
• Focus on Data Governance, Control Assurance, Auditability & Explainability, and Scalable Solutions for risk decision-making.