Requirements

• Strong Backend Engineering: Proven experience building high-throughput, data-intensive systems in any language; hands-on expertise with Kafka, SQL and NoSQL databases; designing for scale and reliability.
• Data Engineering Aptitude: Experience with data quality frameworks, pipeline orchestration, or lineage tracking; understanding what it takes to make 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 working 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 teams—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 for full traceability from risk decisions back to source data.
• Deliver Continuous Assurance: Design and build automated monitoring systems that validate control effectiveness, detecting drift, false positives/negatives, and coverage gaps before incidents occur.
• Enable Auditability: Create audit trail infrastructure and explainability tooling to reduce effort for regulatory reporting and compliance evidence generation.
• Integrate with Risk API: Collaborate closely with the Risk API team to embed governance and assurance into the core platform ensuring clean integration points and shared data contracts.