Senior AI Analytics Engineer
Reap is a stablecoin-native financial infrastructure company providing business accounts, Visa corporate cards, global fiat payments, expense management, and embedded card and payment services.
Funding history
About Reap
Reap is a Hong Kong-founded fintech that bridges traditional finance and digital assets for global businesses. Its platform supports stablecoin-funded corporate cards, business payments settled in fiat, expense controls, treasury operations, and embedded card-issuing and payment infrastructure. Payward completed its acquisition of Reap on July 1, 2026; Reap continues operating as a standalone brand within the Payward ecosystem.
Skills
About the Role
You will own assigned business domains from their data and definitions through dashboards and stakeholder conversations. You will deliver commercial analysis, identify revenue and margin opportunities, build governed AI analytics agents, maintain semantic-layer metrics and dashboards, and enable stakeholders through documentation, training, and support.
Requirements
- 8+ years of analytics engineering or analytics experience with end-to-end business-domain ownership
- Analytical judgment for turning ambiguous business questions into decision-ready answers
- Stakeholder partnership experience with commercial, finance, or risk teams
- Expert SQL skills
- Dimensional modeling and semantic or metrics-layer experience
- Experience with a modern cloud data warehouse and BI tooling
- Financial-data validation, reconciliation, and discrepancy investigation skills
- Documentation and training skills for non-technical stakeholders
- Experience generating pricing, profitability, or growth insights that influence commercial decisions
Responsibilities
- Own business domains from data through dashboards and stakeholder engagement
- Deliver pricing, cost-saving, forecasting, client, and commercial proposal analyses
- Identify revenue opportunities, growth levers, and margin-improvement opportunities
- Build natural-language query AI agents for self-service analytics
- Partner with business teams as embedded decision support
- Convert recurring questions into reusable data, dashboards, or documentation
- Design and maintain vetted views and metric definitions in the Snowflake semantic layer
- Build, validate, reconcile, and debug Metabase dashboards
- Provide documentation, training, office hours, and Slack support
- Collaborate on data ingestion, modeling, priorities, and rollout
