• Serás referencia técnica en arquitectura de medición digital, responsable de diseñar, implementar y mantener los sistemas que garantizan que el dato llega limpio, íntegro y escalable desde cualquier fuente. • Gestionar contenedores GTM (cliente y servidor), diseñando soluciones adaptadas a las limitaciones técnicas de cada cliente. • Implementar y resolver problemáticas en Firebase, Measurement Protocol y server-side tracking. • Desplegar y gestionar contenedores GTM Server-Side garantizando contexto first-party y seguridad del dato. • Modelar datos en BigQuery con SQL para optimización de costes y rendimiento. • Desarrollar scripts para la extracción y carga automatizada de datos desde APIs de terceros. • Garantizar la calidad del dato: integridad, ausencia de duplicidades y rupturas de sesión. • Auditar implementaciones y mantener actualizada la documentación de la arquitectura tecnológica.

• Design and develop new ETL and Business Intelligence Solutions • Monitor and enhance production jobs and legacy ETL processes • Collaborate with existing team for database design and maintenance • Troubleshoot and resolve technical issues while ensuring data security

• Design, develop, and maintain Databricks ETL/ELT pipelines to process Medicaid claims, eligibility, encounters, provider files, and supplemental datasets • Ingest data from MMIS systems, state data warehouses, managed care organizations, and other Medicaid program data sources • Implement transformation, validation, and enrichment logic aligned to Medicaid data quality standards • Optimize Spark jobs for performance and cost efficiency across large Medicaid datasets • Build and maintain Data Lake models for auditability, lineage, and compliance • Develop Power BI semantic models, dashboards, and reports that support Medicaid operations • Collaborate with Medicaid program staff, policy teams, actuaries, and data governance groups

• Partner with business stakeholders to translate domain knowledge into structured analytical and semantic representations. • Design, develop, and maintain enterprise semantic models. • Collaborate with data engineers to shape silver and gold datasets. • Build AI-ready data products by enriching datasets with business definitions and hierarchies. • Develop and optimize Power BI semantic models. • Create and manage standardized KPIs and calculations using DAX. • Document business logic, data definitions, and metric context. • Implement data governance controls. • Publish trusted semantic models and datasets. • Monitor and optimize model performance.