Engenheiro de Dados Sênior SAS

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.