• Design, develop, and maintain high-quality dashboards and reports in Power BI tailored to business needs. • Perform efficient data queries and modeling in SQL and Databricks, ensuring data integrity and performance. • Collaborate on data integration and governance processes across multiple data sources. • Interact with sales, operations, and support teams to understand their processes and translate them into actionable BI solutions. • Support automation and optimization initiatives for reporting to minimize operational overhead. • Document data processes, business definitions, and reporting best practices.

• Take ownership of meaningful metrics and data products, from definition through adoption. • Build and maintain dbt models that define how we measure the business. • Design and maintain dashboards used by growth, finance, and operations to make day-to-day decisions. • Improve data quality through testing, monitoring, and validation. • Enable self-serve analytics so teams can answer their own questions and move faster.

• Structure and evolve the corporate analytics layer, transforming data already available on the platform into reliable, organized, metrics-oriented assets. • Analytics Modeling & Metrics: Develop and evolve dimensional and metric-driven models. • Define and standardize corporate KPIs. • Build data marts oriented to business domains. • Define and maintain a semantic layer for consumption by BI tools and analytical applications. • Document business rules and metric calculations. • Solution and Data Product Development: Design and evolve data products based on certified metrics. • Create analytics-ready datasets for consumption. • Establish reliable data foundations to support AI initiatives and predictive models. • Collaborate with business areas in designing data-driven solutions. • Quality, Governance & Performance: Implement quality tests in the analytics layer. • Ensure traceability and consistency of metrics. • Ensure adequate performance for analytical consumption. • Strategic Engagement: Work closely with Product, Operations and Finance to define strategic metrics.

• dbt at Fora: project structure, conventions, CI/CD, tests, contracts, documentation, and performance. • Data models across bronze, silver, and gold layers. • The semantic layer (dbt MetricFlow or equivalent): metric definitions, dimensions, governance, and adoption. • Production operation of the transformation layer: jobs, dependencies, failures, retries, alerts, environments, and release hygiene. • Python tooling for validation, dbt utilities, lightweight automation, and integrations. • Data quality, test coverage, and observability for modeled tables. • Partnership with Risk & Analytics to formalize business metrics currently spread across SQL, Tableau, and analyst knowledge.