• Diseñar, desarrollar y mantener soluciones de integración y procesamiento de datos en el ecosistema Azure. • Asegurar la disponibilidad, calidad y trazabilidad de la información mediante la construcción y orquestación de pipelines de datos escalables. • Orquestar procesos de integración de datos desde múltiples fuentes, incluyendo bases de datos relacionales, sistemas on-premise, APIs y servicios cloud. • Configurar y administrar Linked Services, Integration Runtime y Self-hosted Integration Runtime. • Implementar procesos de transformación y preparación de datos mediante Mapping Data Flows. • Gestionar la carga y almacenamiento de datos en Azure Data Lake Storage Gen2, Azure Blob Storage, Azure SQL Database y Azure Synapse Analytics. • Desarrollar consultas y procesos de transformación utilizando SQL y Python. • Implementar mecanismos de control de versiones y despliegue continuo mediante Git y Azure DevOps. • Aplicar buenas prácticas de seguridad, gobernanza y acceso a datos utilizando Key Vault, Managed Identities y RBAC. • Monitorear y optimizar el rendimiento de los procesos de integración y carga de datos. • Documentar desarrollos, flujos de integración y procedimientos operativos asociados a las soluciones implementadas.

• Design, build, and maintain ELT/ETL pipelines that move data reliably from source systems into a cloud data warehouse environment. • Write clean, performant, and well-documented SQL to transform raw data into analyst-ready models and reporting layers. • Develop and maintain Power BI dashboards and reports that give business stakeholders clear, trusted views of company performance. • Apply best practices in data modeling within Power BI (star schemas, DAX measures, performance optimization). • Actively use AI tools (such as LLM assistants, copilots, and agentic workflows) to accelerate development and improve code quality. • Engage directly with business stakeholders to understand data needs in context.

• Data Pipeline Support: Assist in building and maintaining scalable ETL/ELT pipelines using AWS Glue, PySpark, and cloud-native services. • BI Reporting & Visualization: Develop and maintain interactive dashboards and reports using Power BI to visualize cloud cost, performance, and operational metrics for stakeholders. • AI/ML Assistance: Support the development and testing of AI agents and machine learning models designed to monitor cloud resource health. • Data Management: Help manage data storage, processing, and query performance using the Snowflake cloud data platform and AWS Athena. • Workflow Orchestration: Learn to orchestrate and monitor data workflows using Apache Airflow DAGs. • Automation: Assist in automating operational workflows using Python and intelligent scripting. • Collaboration: Participate in code reviews, team design sessions, and Agile ceremonies to learn best practices and contribute to team goals. • Documentation: Maintain clear documentation for data processes and assist in tracking project progress via tools like Jira.

• Work with the corporate Enterprise Data & AI and Consumer Data Teams to own the Consumer division’s curated (“silver” and “gold”) data layers, including harmonization of external market data with corporate sources, in alignment with enterprise lakehouse and governance standards • Drive data “AI-readiness” to help future-proof the data ecosystem, inclusive of metadata curation and documentation of business logic • Develop and operate the Consumer BI ecosystem on the corporate lakehouse platform (e.g., PowerBI, Databricks), enabling scalable self-service by analysts and business users • Enable integration of AI into business reporting and underlying analysis, in order to build early warning systems and to identify underlying business trends worthy of future study • Partner with Consumer division leadership to ensure downstream analysis applications and BI stack are delivering reliable, efficient, and valuable service