Engenheiro de Dados

Accountabilities:

• • 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.

  Requirements:

  • 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.

  Benefits:

  • 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.