Compliance at a major international bank like RBI runs on data. Sanctions screening, AML transaction monitoring, KYC — these are legal obligations with real consequences if the data is wrong or missing. For a long time, daily data was good enough. But the world has moved on: compliance teams need data faster, fresher, and in better quality. Our team is driving that shift — building the architecture that makes compliance data available in real-time, at the push of a button.
This is hands-on work with a modern stack. Events stream in through Apache Pulsar, get processed and enriched, land in Databricks and surface as compliance insights in Power BI. We translate what compliance teams need in their data products — and we keep expanding that product portfolio. There is no shortage of interesting problems here. Promised!
If you want to work at the intersection of compliance and data engineering, get close to a live event streaming architecture, and see your work directly used by compliance teams across RBI Group — this is the right team.
Act as the bridge between compliance and engineering, aligning stakeholders with different priorities and ensuring discussions remain productive and outcome-driven
Contributing to our team spirit - we are an international, distributed team and we make that work
Translate requirements across AML transaction monitoring, KYC, case management, and reporting into structured data product specifications (schemas, field definitions, business rules, and measurable data quality criteria)
Analyze end-to-end data flows across our event-driven architecture (Apache Pulsar Databricks) and identify gaps between stakeholder needs and current data products
Lead requirements discovery and backlog refinement together with product, engineering, and reporting stakeholders
Own data quality monitoring requirements: define freshness, completeness, and correctness thresholds and drive incident resolution and root-cause analysis with engineering
Design and execute test cases for data pipeline deliveries, validating mappings, transformations, and completeness before go-live
Strong understanding of data modelling and data architecture concepts, ideally in BI, analytics, or data platform environments
Curious, with a sense of humour, and motivated to improve the architecture, processes, and tools you work with
You treat AI tools as force multipliers: using them actively in analysis, documentation, and validation, while applying sound judgment to outputs
Experience in a business analyst or data analyst role, preferably in financial services, banking, or compliance
Ability to write precise, testable acceptance criteria and clear data quality definitions (completeness, freshness, correctness)
Comfortable working across technical and business discussions, with the ability to build common ground between stakeholders with different perspective
Structured and self-reliant working style, taking end-to-end ownership and driving topics to completion
Proactive and team-oriented, surfacing blockers early and coming with solutions, not just problems
You understand agility as a mindset, not a framework — and apply it pragmatically in your daily work
Strong English skills for collaboration across RBI
