Databricks Data Engineer | Senior

**This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Databricks Data Engineer | Senior based in Brazil.** We are looking for a Senior Data Engineer to support the evolution of a modern enterprise data platform, helping organizations build scalable, reliable, and high-performance data solutions. This role focuses on designing and implementing Lakehouse architectures, modernizing analytical ecosystems, and enabling data-driven decision-making. The professional will work with advanced cloud technologies, Databricks, Apache Spark, and Data Engineering best practices to transform complex data environments. You will contribute to large-scale platform modernization initiatives, including cloud migrations and the evolution of legacy data pipelines. This position requires strong technical expertise, a collaborative mindset, and the ability to solve complex data challenges in distributed environments. It is an opportunity to work on impactful projects involving DataOps, governance, automation, and next-generation data architectures. ### Accountabilities: The Senior Data Engineer will be responsible for designing, developing, and evolving enterprise-scale data solutions, ensuring reliability, scalability, and governance across the data ecosystem. Main responsibilities include: - Support the implementation and evolution of a corporate Data Platform based on Enterprise Lakehouse architecture. - Contribute to the modernization of analytical ecosystems, including migration of workloads between cloud environments and Databricks platforms. - Develop, maintain, and optimize scalable, reliable, and high-performance data pipelines. - Build data ingestion, transformation, and delivery solutions using modern Lakehouse architecture patterns. - Apply Data Engineering best practices, including DataOps, CI/CD, automation, and code versioning. - Support data governance, quality management, and data cataloging initiatives. - Modernize legacy pipelines using Apache Spark and Databricks technologies. - Design and implement solutions for complex integrations between enterprise systems and distributed data environments. - Collaborate on the development of Data Lake, Data Warehouse, and Lakehouse architectures in cloud environments. - Ensure data solutions meet requirements for performance, security, reliability, and scalability. ## Requirements: We are looking for a professional with strong experience in Data Engineering, cloud platforms, and modern data architectures, capable of working with large-scale data environments and complex enterprise integrations. - Advanced knowledge of SQL. - Experience building and maintaining ETL/ELT pipelines. - Hands-on experience with Databricks. - Strong knowledge of Apache Spark for distributed data processing. - Experience with Data Lake, Data Warehouse, and/or Lakehouse architectures. - Knowledge of analytical and dimensional data modeling. - Experience processing large volumes of data. - Experience working with cloud environments, preferably AWS. - Knowledge of AWS services such as Glue, Unity Catalog, and Lake Formation. - Experience with Git and software versioning practices. - Knowledge of CI/CD practices applied to Data Engineering. - Experience with tools such as Airflow, Kafka, and dbt. - Knowledge of SQL and NoSQL databases, including PostgreSQL, MongoDB, and Cassandra. - Experience with modernization projects and migration of enterprise data platforms. - Ability to work with complex system integrations and distributed architectures. ## Benefits: - Opportunity to work on large-scale data transformation and modernization projects. - Remote work flexibility. - Exposure to advanced technologies including Databricks, Apache Spark, cloud platforms, and Lakehouse architectures. - Professional growth opportunities in Data Engineering and emerging technology environments. - Collaborative culture focused on innovation and continuous learning.…