Pessoa Especialista em Engenharia de Dados Sênior

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Pessoa Especialista em Engenharia de Dados Sênior based in Brazil. We are looking for a Senior Data Engineering Specialist to design, build, and evolve scalable data architectures that support strategic business decisions and innovation. In this role, you will work across Data Lake, Data Warehouse, and Lakehouse environments, ensuring data quality, security, governance, and reliability at scale. You will develop and optimize sophisticated data pipelines, enabling the efficient integration and processing of large volumes of information. As a technical expert, you will establish engineering standards, promote best practices, and improve the performance of data platforms and workflows. Working closely with multidisciplinary teams, you will help translate business needs into robust, sustainable data solutions. This fully remote opportunity is ideal for an experienced professional who combines deep technical expertise, architectural vision, and a passion for building high-quality data ecosystems. Accountabilities: - Design, build, and maintain scalable data ingestion, transformation, and integration pipelines to support reliable data processing across the organization. - Develop and evolve robust architectures for Data Lakes, Data Warehouses, and Lakehouse environments, ensuring scalability, performance, and long-term maintainability. - Implement and optimize ETL/ELT processes to improve data processing efficiency, reliability, and resource utilization. - Establish and enforce data quality, governance, security, and management standards throughout the data lifecycle. - Integrate multiple data sources and destinations, ensuring interoperability and consistent data availability across platforms and systems. - Apply distributed processing technologies to handle large datasets efficiently and support complex analytical workloads.

- Define technical standards, architectural guidelines, and engineering best practices to promote consistency and excellence across data engineering initiatives. - Monitor, troubleshoot, and optimize data pipelines and platform components to maintain performance, accuracy, and operational reliability. - Collaborate with multidisciplinary teams to understand business requirements and translate them into scalable, effective data solutions. - Contribute to the continuous improvement of data infrastructure, architectures, and engineering processes, encouraging innovation and the adoption of modern technologies. Requirements: - Advanced proficiency in SQL, including the ability to manipulate, transform, and analyze large volumes of data efficiently. - Strong professional experience with Python or Scala for data engineering, pipeline development, and data processing automation. - Proven hands-on experience with Apache Spark and distributed data processing technologies. - Deep knowledge of Data Lake, Data Warehouse, and Lakehouse architectures, including their design, implementation, and optimization. - Extensive experience developing, maintaining, and optimizing ETL/ELT pipelines in cloud-based environments. - Advanced knowledge of data modeling, data governance, data quality management, and scalable data architecture principles. - Practical experience with cloud platforms such as Microsoft Azure, Amazon Web Services (AWS), or Google Cloud Platform (GCP). - Strong understanding of data integration patterns, pipeline orchestration, and reliable data processing workflows. - Ability to define technical standards, evaluate architectural alternatives, and recommend solutions that balance performance, scalability, security, and cost. - Strong analytical and problem-solving skills, with the ability to troubleshoot complex data engineering challenges.