Engenheiro de Dados in Brazil at Jobgether

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

This is an opportunity to help transform data into valuable insights by contributing to the evolution of modern data and analytics platforms.
You will design and maintain data pipelines, integrate information from multiple sources, and build reliable analytical environments that support business decisions.
The role combines data modeling, engineering, cloud technologies, and modern processing frameworks in a collaborative technology environment.
You will work with large and diverse datasets while applying strong practices around data quality, governance, performance, and reliability.
Your contributions will directly support the development and modernization of data capabilities and analytics solutions.
You will collaborate within agile teams and apply DevOps/DataOps practices to deliver scalable and sustainable data products.
The position requires on-site or hybrid work in Blumenau and offers opportunities for continuous learning and professional development.

• Implement and maintain integrations between multiple data sources, ensuring reliable and efficient data flows.
• Design, develop, and maintain analytical environments that provide trusted data for reporting, analytics, and business decision-making.
• Contribute to the evolution and modernization of data platforms, supporting projects involving new architectures, technologies, and capabilities.
• Develop, maintain, monitor, and troubleshoot data pipelines using Python, SQL, ETL/ELT processes, and modern data engineering practices.
• Apply data modeling techniques to support BI and analytics environments, including Data Warehouses, Datamarts, and Data Lakes.
• Build scalable data processing solutions capable of handling large volumes of information, including the use of Apache Spark.
• Work with cloud-based environments and modern data architectures to improve scalability, performance, and reliability.
• Monitor and sustain production data pipelines, proactively identifying and resolving operational issues.
• Apply principles of data quality, governance, security, and performance throughout the data lifecycle.
• Collaborate with agile teams and contribute to DevOps and DataOps practices, including continuous improvement and efficient delivery processes.
• Participate in initiatives focused on the modernization, optimization, and continuous evolution of data platforms.
• Work collaboratively with technical and business stakeholders to understand requirements and deliver solutions aligned with organizational priorities.

• Proven experience with data modeling for BI and analytics environments.
• Strong practical knowledge of Data Warehouse, Datamart, and Data Lake concepts and architectures.
• Advanced SQL skills, including data querying, transformation, optimization, and performance considerations.
• Hands-on Python development experience for building and maintaining data pipelines.
• Experience with ETL and ELT processes and data integration patterns.
• Experience with Apache Spark and distributed processing of large datasets.
• Demonstrated experience building, monitoring, troubleshooting, and supporting data pipelines in production environments.
• Understanding of data quality, governance, security, and performance principles.
• Experience working with cloud environments and modern data architectures.
• Experience working in agile teams and familiarity with DevOps or DataOps practices.
• Availability to work in a presential/hybrid model in Blumenau, Brazil.
• Experience in financial services or credit cooperative environments is desirable.
• Knowledge of Databricks is a plus.
• Experience with AWS and its data services is advantageous.
• Familiarity with Azure DevOps for demand management and CI/CD is desirable.
• Knowledge of Git and software version-control best practices is beneficial.
• Experience participating in data-platform modernization projects is a plus.
• Understanding of financial-sector data regulations, security, and governance is desirable.
• Strong collaboration, problem-solving, organization, and continuous-learning skills.

• Competitive benefits package.
• Medical assistance.
• Dental assistance.
• Private pension plan.
• Profit-sharing / results-based participation.
• Flexible meal and/or food allowance.
• Transportation allowance with no employee discount.
• Childcare or nanny assistance.
• Life insurance.
• Private pension and long-term financial planning support.
• Individual Development Plan focused on career growth.
• Investment in education and access to learning opportunities.
• Extended support and benefits for significant personal and family occasions.
• Recognition programs for employee tenure and contribution.
• Wellness and quality-of-life initiatives.
• Collaborative work environment with opportunities for professional development.
• Hybrid work model in Blumenau.
• Inclusive workplace committed to diversity, equity, accessibility, and respect.