• Building and maintaining the core data infrastructure that powers analytics across the company. • Designing pipelines and data models that pull from product systems, observability tooling, and external sources into a reliable, scalable data platform. • Working closely with SRE, product, and engineering teams to ensure data is correctly captured, structured, and aligned across services. • Maintaining observability stacks to support debugging and system reliability. • Defining and enforcing data quality standards. • Supporting KPI development and ensuring all pipelines and data flows meet security, privacy, and compliance requirements.

• Support the development and maintenance of data pipelines (ETL/ELT) under the supervision of more experienced engineers; • Assist in structuring and preparing data in analytical environments (Data Lake and Lakehouse); • Help create and maintain databases, tables, and views, becoming familiar with data modeling patterns (star schema, snowflake); • Contribute to data ingestion, transformation and cleansing routines; • Collaborate with other data team members and business areas to facilitate access to and availability of information; • Follow the security, privacy, and compliance guidelines and best practices (including LGPD) defined by the team; • Support documentation of processes, pipelines and data dictionaries; • Use version control (Git) in daily deliveries; • Actively participate in agile ceremonies (Scrum), contributing to sprint deliverables with commitment and on schedule.

• Diseñar e implementar arquitecturas de datos escalables (ETL/ELT) • Construir y mantener tuberías de datos para ingestión, procesamiento y consumo • Desarrollar API y servicios de datos para soportar análisis y casos de uso de productos • Trabajar con AWS y/o Azure para implementar plataformas de datos modernas (lagos de datos, almacenes, streaming) • Automatizar flujos de trabajo de datos con enfoque en resiliencia, observabilidad y rendimiento • Colaborar con Científicos de Datos, Analistas y equipos de Producto para llevar modelos a producción • Participar en decisiones de arquitectura y revisiones de código • Explorar e implementar tendencias emergentes (Data Mesh, MLOps, RAG, etc.)

• Design and implement modern data warehouse architectures • Lead data migration and modernization of existing DWH systems • Analysis and translation of business and technical requirements into scalable, architecture-compliant solutions • Collaborate closely with internal stakeholders and cross-functional teams • Ensure data governance, security, and compliance with Swiss regulatory requirements • Continuously develop and optimize data platforms and reporting solutions • Development and enforcement of naming conventions, self-service approaches and boundaries, tool recommendations, and guidelines