Engenheiro de Dados Pleno

This role focuses on building reliable, scalable data foundations for modern AI and analytics solutions. You will design and operate ETL/ELT pipelines using Databricks, Delta Lake, and lakehouse architectures. The position combines structured and unstructured data engineering, including the ingestion and preparation of PDFs, images, and text for RAG and evaluation workflows. You will contribute to data curation, anonymization, vector indexing, embeddings, and versioned datasets. The role also involves connecting data platforms with inference services and APIs while balancing performance, cost, monitoring, and reliability. Automation, data quality, CI/CD, and continuous improvement will be central to your work. You will join a dynamic, technology-focused environment where modern cloud and AI practices are used to solve complex business challenges.

The ideal candidate combines strong data engineering fundamentals with practical Databricks and cloud experience, plus an understanding of modern data and AI workflows.

• Advanced Python and SQL skills.
• Solid knowledge of data modeling and medallion/lakehouse architecture.
• Experience building data pipelines for unstructured data, including PDFs, images, and text, and preparing these datasets for RAG applications.
• Familiarity with vector databases and embeddings, such as Databricks Vector Search, pgvector, or similar technologies.
• Experience with data quality, data testing, and versioning practices.
• Hands-on experience with Databricks, including Delta Lake, Workflows/Jobs, notebooks, PySpark, and Spark SQL.
• Experience with Git and CI/CD practices.
• Professional experience working in cloud environments such as Azure, AWS, or GCP.
• Knowledge of LGPD and the appropriate handling of sensitive data.
• Experience with Unity Catalog in governed environments is desirable.
• Familiarity with MLflow, Databricks Model Serving, or Mosaic AI is a plus.
• Experience with Delta Live Tables, Lakeflow, or Auto Loader is desirable.
• Experience in insurance or financial services environments is an advantage.
• Familiarity with Terraform or Databricks Asset Bundles is a plus.
• Databricks Data Engineer Associate or Professional certification is desirable.
• Proactive approach, problem-solving mindset, adaptability, and willingness to continuously learn new technologies.