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.

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.