Implement, configure, and test decision engine process flows and rule changes. Execute QA, A/B tests, and historical backtesting. Validate data integrity between vendors and core apps. Gather requirements, document processes, and collaborate with Pricing, Risk, and Engineering to ensure accurate, efficient decisioning.

Design, build, and maintain scalable dimensional data models, semantic layer, and production transformation pipelines. Collaborate with Data Engineering, Data Science, BI, DevOps, and Product to enable AI-ready data, ensure data quality and governance, support ML feature delivery, and coach analytics team members for robust, production-ready data products.

Lead and grow a team of analytics engineers while remaining hands-on with SQL, dbt, and Snowflake. Own roadmap and semantic layer development, build trusted, governed data products, partner with cross-functional stakeholders, champion data quality and observability, and hire and coach engineering talent to deliver scalable analytics and AI-ready foundations.