Data Engineer

Familiarity with agile methodologies; Experience in Databricks, SQL, Python, ETL/ELT, Data Modeling, Data Lake, Data Warehouse and data visualization tools; Knowledge on AWS Cloud Watch, KMS, Glue, lambda, S3, redshift, snowflake, jenkins, gitlab, denodo, kubernetes; High learning ability.Preferred Qualifications: Experience in the international projects is an advantage; Fluent in Portuguese and English (written & spoken). Write technical design docs; Manage databricks environment; Manage AWS, Azure and GCP cloud components; Develop solutions using (Java/Python/Spark/Scala); Configure network components in hybrid environments; Define best practices for relational and non-relational data storage; Implementation of improvements in Data Lake and Data Warehouse environments; Implement and manage SQL and NoSQL databases; Definition and development of DevOps, Docker and Kubernetes solutions; Discuss and define best solutions for system integrations; Support the creation of data governance processes; Discuss best solutions to support the self-service BI strategy in the company.