• Partner closely with operational and analytics teams to translate business needs into analytics-ready data models, curated data marts, and reusable datasets. • Build and maintain dbt projects (staging → intermediate → marts), including model layering, macros, exposures, packages, and source freshness to accelerate delivery and improve reliability. • Design and evolve dimensional models (facts/dimensions, grain, SCD patterns) and analytics patterns aligned with key business domains. • Own metrics definitions end-to-end: establish KPI logic, naming standards, calculation rules, and governance; maintain a metrics/semantic layer so stakeholders use consistent definitions across tools and teams. • Implement robust data quality practices (dbt tests, constraints, anomaly checks/monitoring) to ensure reliable downstream reporting and decision-making. • Produce clear documentation and enablement assets (dbt docs, lineage, data dictionaries, metric definitions, onboarding guides) to support self-service analytics. • Optimize warehouse performance and cost in Snowflake through SQL tuning, incremental models, appropriate materializations, and efficient data design. • Use disciplined software engineering practices (Git-based workflows, peer review, CI checks, versioning, environment promotion) to deploy changes safely and repeatably. • Proactively identify and resolve data-related issues, ensuring system reliability and data integrity. • Provide ongoing support for critical analytics data products and participate in an on-call rotation as needed. • Responsible for adherence to the Capital Rx Code of Conduct including reporting of noncompliance.