Engenheiro(a) de Dados

Accountabilities

• Design, implement, and continuously improve scalable, secure, and efficient data architectures.

• Develop, maintain, and optimize ETL/ELT pipelines for data ingestion, integration, processing, transformation, and delivery.

• Build and maintain Data Lake, Data Warehouse, and analytical environments to support business intelligence and advanced analytics.

• Ensure data quality, traceability, security, governance, and compliance with established standards and best practices.

• Integrate data from multiple enterprise systems, applications, and corporate sources, ensuring consistency and reliability.

• Optimize data storage, processing, transformation, and consumption to improve performance, scalability, and cost efficiency.

• Contribute to the definition and implementation of data architecture standards, engineering practices, and modern cloud-based data strategies.

• Collaborate with business teams, analytics, BI, data science, and technology professionals to deliver data-driven solutions aligned with organizational needs.

• Provide technical guidance and act as a reference for data engineering initiatives, supporting multidisciplinary teams and knowledge sharing.

• Participate in the design, implementation, and continuous evolution of modern data and analytics platforms.

Requirements:

• Bachelor's degree in Information Technology, Data Science, Engineering, Mathematics, Statistics, Physics, Chemistry, or a related field.

• Professional experience in Data Engineering and the design of data architecture solutions.

• Strong knowledge of data modeling, systems integration, and modern data management practices.

• Hands-on experience building, maintaining, and optimizing ETL/ELT pipelines.

• Advanced SQL skills and experience processing and transforming large volumes of data.

• Understanding of data governance, data quality, security, and traceability principles.

• Practical experience working with Data Lake and Data Warehouse environments.

• Knowledge of cloud platforms and cloud-based data services.

• Strong analytical and problem-solving skills, with the ability to collaborate effectively with technical teams and business stakeholders.

• Good communication skills, a proactive approach, and the ability to contribute to multidisciplinary projects.

Nice to have:

• Databricks certifications or specialized training.

• Experience with SAP Datasphere, Cognite, or Dataiku.

• Python proficiency for data engineering, workflow automation, and process optimization.

• Experience designing or implementing modern data and analytics architectures.

• Previous experience in technical leadership, mentoring, or coordinating data teams.

• Familiarity with DataOps practices, Git, version control, and agile methodologies.

Benefits:

• Work model:Fully remote, offering flexibility to work from Brazil.

• Employment type:Full-time employee position.

• Accessibility:The opportunity is also open to persons with disabilities (PwD).

• Professional development:Exposure to modern data architectures, cloud technologies, and evolving data engineering practices.

• Collaborative environment:Opportunities to work with multidisciplinary teams across business, analytics, and technology.

• Technical growth:Opportunities to contribute to architectural decisions, share expertise, and support the evolution of data platforms.