Contribute to structuring and evolving Data Lake environments, ensuring data scalability and governance;
Design and build modern, modular data warehouses prepared for growth and high performance;
Develop data schemas and resilient architectures, following data engineering best practices;
Define and evolve data architecture, ensuring reliable, scalable, and well-structured environments;
Perform exploratory data analysis and support the development of predictive models;
Participate in building data-driven recommendation engines and processes;
Support business squads with structured, reliable, production-ready data that delivers value;
Act as a technical reference, mentoring and developing more junior professionals;
Collaborate actively with the team to solve complex problems and turn data into actionable decisions.

Experience developing ETL architectures;
Knowledge of architectures for performance improvement and data operations;
Practical knowledge of operational and relational data management;
Previous experience with DataOps;
Practical knowledge of programming languages and algorithms (Python, TensorFlow);
Experience in data development and operations, including integration and operationalization with Docker and/or Kubernetes;
Experience in projects using Databricks;
Bachelor's degree in IT or a related field.

Data Engineer (Mid/Senior) – Databricks

Key skills