• 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

Please submit your CV in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment. About the Role This project is suited for a Senior Python developer with deep functional testing experience, strong Linux and Docker skills, the ability to read code across multiple languages with the support of LLMs (e.g., C, Rust, Go) and translate requirements for migration tasks, and confidence using tools like Roo Code or Claude Code to accelerate iterative development. Key Responsibilities - Create functional black box tests for large codebases in various source languages - Create and manage Docker environments to ensure 100% reproducible builds and test execution across different platforms - Monitor code coverage and configure automated scoring criteria to meet industry benchmark-level standards - Leverage LLMs (Roo Code, Claude) to accelerate development cycles, automate repetitive tasks, and improve overall code quality