• Model and implement the data warehouse and a data lake on S3. • Implement an offline Feature Store (SQL Server, point-in-time correctness) and an online Feature Store (Redis). • Develop ETL/ELT pipelines with versioning, data lineage, and data quality tests. • Evolve existing pipelines and analytical dashboards as the starting point for the data lake. • Integrate event-driven architecture (Azure Service Bus / Kafka) for real-time features. • Support MLOps pipelines (Azure ML, MLflow) in collaboration with ML Engineers.

• Work on an SAP Commerce migration project, supporting the adaptation of the new SAP Commerce platform to the current data flows; • Perform maintenance and adjustments on existing pipelines, following directions and priorities defined by the client; • Contribute to the continuity of data migration and integration initiatives related to the project; • Support requests that fall outside the project's initial scope, ensuring the evolution and stability of data flows; • Participate in the analysis, correction, and enhancement of existing data processes; • Collaborate with the team on the maintenance and adaptation of solutions during the technological transition period.

• Diseñarás, desarrollarás y optimizarás pipelines y soluciones de datos escalables, fiables y mantenibles en entornos modernos de Data Warehouse, trabajando principalmente sobre Snowflake • Participarás en el diseño e implementación de modelos y soluciones de datos eficientes, aplicando buenas prácticas de modelado, transformación ELT, calidad, gobierno y rendimiento, con foco en la escalabilidad, mantenibilidad y evolución futura de las soluciones • Identificarás oportunidades de mejora continua en procesos, consultas, cargas, modelos, costes y flujos de integración, contribuyendo a la evolución de la plataforma de datos • Trabajarás de forma cercana con equipos de negocio y otras áreas técnicas para entender requisitos, traducirlos en soluciones robustas y asegurar la entrega de datos fiables, trazables y preparados para el consumo

• You design and own the architecture of our end-to-end data platform — from data integration and transformation to data delivery • You lead the development of robust data pipelines using Fivetran, Airbyte and Python, setting technical standards for the team • You drive outstanding data modeling in Databricks and apply advanced SQL, dbt and data-quality frameworks such as elementary • You define and establish standards for data quality and ensure reliable data marts that serve as the basis for business-critical decisions • You provide technical leadership and work closely with the Product Owner and the Business Insights team on complex data challenges • You are responsible for the ongoing development of our cloud infrastructure on AWS and advance Infrastructure as Code (IaC) using Terraform