Engenheiro de Dados Sênior SAS

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Engenheiro de Dados Sênior SAS based in Brazil.

This is a senior data engineering role focused on modernizing SAS-based data solutions and accelerating their transition to cloud-native <architectures.You> will design, develop, and optimize scalable data pipelines across Azure and Databricks environments.A key part of the role is translating SAS processes and analytical workloads into efficient Python and PySpark <solutions.You>’ll contribute to cloud migration initiatives while ensuring data quality, security, governance, and performance.The position involves close collaboration with business, data science, and technology teams, including AI-focused <initiatives.You>’ll work with modern DataOps, DevOps, and MLOps practices in an environment focused on continuous innovation.This is an opportunity to play a strategic role in transforming legacy data ecosystems into scalable, governed cloud platforms.

Accountabilities

• Develop and maintain scalable ETL/ELT data pipelines in Azure, using Databricks for large-scale data processing and integration.
• Define and implement strategies, standards, and best practices for migrating SAS code and processes to Python/PySpark.
• Provide technical support for the migration and modernization of SAS routines, analytical processes, and solutions into Databricks.
• Read, understand, assess, and migrate existing SAS workloads while ensuring functional and data consistency.
• Design and optimize data models and architectures to support scalability, performance, maintainability, and governance.
• Work with medallion architecture principles across Data Lake and Data Warehouse environments.
• Implement CI/CD practices and code versioning using GitHub, supporting automated and reliable deployments.
• Support cloud migration projects while ensuring data security, quality, integrity, and operational continuity.
• Collaborate with business and data science teams to support the deployment of AI models and data solutions in cloud environments.
• Apply data profiling, quality checks, monitoring, and governance practices to maintain reliable and consistent datasets.
• Document data architectures, processes, migration strategies, technical decisions, and engineering best practices.
• Contribute to DevOps, DataOps, and MLOps initiatives and identify opportunities to automate and improve data pipelines.
• Support data ingestion and integration initiatives, including API-based integrations where applicable.

Requirements

• Solid professional experience in data engineering, with strong expertise in Azure Data Services and Databricks.
• Hands-on experience with SAS, including the ability to read, understand, assess, and migrate SAS code and processes.
• Proven experience defining strategies and standards for converting SAS workloads to Python/PySpark.
• Strong experience supporting the migration of SAS analytical processes and solutions to Databricks.
• Hands-on expertise with Databricks and PySpark.
• Strong knowledge of Python and SQL for data manipulation, transformation, and analysis.
• Experience with medallion architecture, Data Lakes, and/or Data Warehouses.
• Solid understanding of ETL/ELT processes and integration of large data volumes.
• Experience with data modeling across conceptual, logical, and physical levels.
• Knowledge of CI/CD, GitHub, and automated deployment practices.
• Experience participating in cloud migration projects.
• Familiarity with DevOps, DataOps, and MLOps practices and workflows.
• Understanding of data governance and data quality principles in cloud environments.
• Strong analytical and problem-solving skills, with the ability to work across legacy and modern technology environments.
• Excellent collaboration and communication skills when working with business, engineering, data science, and technology stakeholders.
• Experience with AI projects and pipeline automation is a plus.
• Experience integrating data through SAP Ariba APIs is desirable.
• Knowledge of Hive and Teradata, particularly in legacy modernization initiatives, is an advantage.

Benefits

• Health and dental insurance.
• Meal and food allowance.
• Childcare assistance.
• Extended parental leave.
• Partnerships with fitness and health professionals through Wellhub (Gympass) and TotalPass.
• Profit-sharing program (PLR).
• Life insurance.
• Continuous learning platform and professional development opportunities.
• Partnerships with online learning platforms.
• Language-learning platform.
• Discount club and partner benefits.
• Online platform focused on physical health, mental health, and overall well-being.
• Pregnancy and responsible-parenting courses.
• Inclusive workplace with dedicated health, well-being, and inclusion support.
• Opportunities to collaborate with multidisciplinary and international technology teams.
• Continuous exposure to cloud, data engineering, AI, and modern engineering practices.
• For professionals residing in the Campinas Metropolitan Region, office attendance may be required according to the applicable workplace policy.