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.

How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best!  Why Apply Through Jobgether?    Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.     #LI-CL1