Senior Data Engineer (AI Data Platform)

Accountabilities: Design, develop, and maintain scalable data architectures, data models, and cloud-native data platforms. Build and optimize ETL and data ingestion pipelines following Medallion Architecture principles (Bronze, Silver, Gold). Develop and maintain data warehouse solutions using Snowflake and implement transformation workflows using dbt. Create and manage orchestration pipelines leveraging Dagster or similar workflow management technologies. Manage and optimize cloud-based data storage solutions, particularly within AWS environments. Design and maintain graph-based data structures and support entity matching pipelines where applicable. Collaborate closely with AI, Data Science, and Engineering teams to ensure reliable and efficient data consumption for AI applications. Provide technical leadership, promote best practices in data engineering, and contribute to continuous improvement initiatives within Agile teams. Requirements Bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related field, or equivalent professional experience. Minimum of 5 years of experience in Data Engineering or similar roles. Strong expertise in designing scalable data architectures, data models, and modern data platforms. Hands-on experience with Snowflake, dbt, advanced SQL, and ETL pipeline development. Proven experience implementing Medallion Architecture and cloud-native data engineering practices. Experience with AWS services, particularly S3, and workflow orchestration tools such as Dagster. Practical experience with PostgreSQL and/or Supabase environments. Familiarity with graph databases and AI/ML concepts, including embeddings and AI-driven data workflows. Strong analytical, problem-solving, and communication skills, with experience working in collaborative software development environments. Upper-Intermediate to Advanced English proficiency (B2+/C1). Benefits Fully remote opportunity based in Brazil. Exposure to innovative AI-driven projects and modern data engineering technologies. Collaborative, high-performance, and learning-oriented work environment. Opportunity to work alongside multidisciplinary teams across data, AI, cloud, and software engineering domains. Strong culture of technical ownership, transparency, and continuous professional growth. Participation in impactful projects that drive business transformation through data and artificial intelligence. Possibility of contract extension beyond the initial 6-month engagement period.