• Build foundational analytical constructs in Python • Develop reusable Python modules that transform structured datasets into analytical building blocks used across the platform • Create structured analytical outputs that AI systems can reliably interpret • Develop analytical tools that allow the platform’s conversational interface to answer data questions reliably • Collaborate with data platform teams to consume structured datasets from environments such as Databricks • Implement validation logic to ensure analytical outputs reconcile with underlying datasets • Design analytical outputs that maintain clear traceability between source data, analytical computations, and AI-generated explanations

• Facilitar la ideación y creación de soluciones analíticas para diversas funciones. • Capturar requerimientos y sugerir mejoras en los procesos analíticos. • Colaborar ampliamente con equipos multifuncionales y en toda la organización. • Impulsar el desarrollo y la implementación de soluciones analíticas, fomentando el análisis y los insights que generen resultados positivos para el negocio. • Asegurar que el desarrollo de Analytics & Insights esté alineado con los procesos End-to-End (E2E) y los objetivos del negocio. • Actuar como un recurso clave para apoyar e impulsar iniciativas analíticas. • Garantizar un alto nivel de valor y satisfacción del cliente mediante una responsabilidad extrema. • Promover la adopción y el uso de herramientas e insights analíticos. • Brindar soporte en la capacitación sobre herramientas analíticas. • Asegurar la entrega oportuna y eficiente de soluciones. • Servir como guardián de la analítica generando insights para casos de uso del negocio

• Partner with teams across Finance, Engineering, Sales, Product, Marketing, and Customer Success to uncover their workflows, challenges, and data needs. • Design, build, and maintain scalable dbt models and data pipelines supporting financial reporting (ARR, billing, revenue recognition) as well as operational, product, and GTM analytics. • Tackle ambiguous, high-complexity problems, untangling systems, manual processes, and unclear logic to produce clear, durable data solutions. • Translate user challenges and incomplete requirements into structured data models, automated workflows, and end-to-end solutions. • While building towards automation, understanding the user needs to process manual tasks. • Own solutions from ingestion to transformation to data quality, documentation, and stakeholder enablement. • Connect data and logic across domains, identifying how systems relate and surfacing opportunities to simplify, standardize, or automate. • Advocate for high standards in data quality, clarity, documentation, and maintainability.

• Partner with teams across Finance, Engineering, Sales, Product, Marketing, and Customer Success to uncover their workflows, challenges, and data needs. • Design, build, and maintain scalable dbt models and data pipelines supporting financial reporting (ARR, billing, revenue recognition) as well as operational, product, and GTM analytics. • Tackle ambiguous, high-complexity problems, untangling systems, manual processes, and unclear logic to produce clear, durable data solutions. • Translate user challenges and incomplete requirements into structured data models, automated workflows, and end-to-end solutions. • While building towards automation, understand the user needs to process manual tasks. • Own solutions from ingestion to transformation to data quality, documentation, and stakeholder enablement. • Connect data and logic across domains, identifying how systems relate and surfacing opportunities to simplify, standardize, or automate. • Advocate for high standards in data quality, clarity, documentation, and maintainability.