Engenheiro de Dados Sênior Databricks/DBT

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

This is a senior-level opportunity to help build and evolve a modern data platform centered on dbt and Databricks.

You will play a key role in defining the platform’s architecture, engineering standards, scalability, governance, and reliability.

The position combines data engineering with strong software engineering, DevOps, and CI/CD practices.

You will work across data modeling, pipeline automation, cloud infrastructure, performance optimization, and data security.

The role offers significant technical ownership, including the evolution toward dbt Fusion and dbt Core 2.0.

You will collaborate with an agile team while mentoring peers and promoting engineering best practices.

This is a fully remote environment suited to professionals who enjoy solving complex data-platform challenges and driving technical evolution.

Accountabilities

• Design and implement the dbt platform architecture on Databricks, including Unity Catalog and medallion architecture across bronze, silver, and gold layers.
• Establish DBT project standards covering data modeling, naming conventions, staging/intermediate/mart layers, macros, testing, packages, and documentation.
• Apply dimensional modeling approaches such as Kimball/star schema and, when appropriate, Data Vault.
• Build and maintain CI/CD pipelines for data projects using GitHub Actions, covering validation, builds, automated testing, and deployment across development, staging, and production environments.
• Automate infrastructure provisioning and platform operations using Terraform and Databricks Asset Bundles.
• Develop and maintain Databricks Workflows for reliable data-pipeline orchestration.
• Establish reproducible environments through Git-based version control and collaborative development workflows such as GitFlow or trunk-based development.
• Optimize data-platform performance and costs across clusters, SQL Warehouses, Photon, partitioning strategies, and incremental processing.
• Work with Delta Lake, Parquet, Apache Spark, and PySpark to support distributed data-processing requirements beyond SQL.
• Define and implement data governance and security practices using Unity Catalog, access controls, and sensitive-data masking.
• Ensure data-platform practices support LGPD requirements and broader privacy and compliance standards.
• Mentor team members in analytical engineering practices, review pull requests, and maintain high technical quality across deliveries.
• Identify opportunities to improve automation, observability, reliability, and the overall developer experience of the data platform.

Requirements

• Minimum 4 years of hands-on experience with dbt Core, including incremental models, snapshots, Jinja macros, tests, packages, and exposures.
• Minimum 4 years of practical experience with Databricks, including Unity Catalog, SQL Warehouses, clusters, Delta Lake, and Workflows.
• Strong knowledge of Apache Spark and distributed data processing.
• Advanced SQL and Python skills, with the ability to develop reliable and maintainable data solutions.
• Practical experience implementing CI/CD for data pipelines using GitHub Actions.
• Experience with Databricks Asset Bundles for packaging and deploying data-platform components.
• Strong Git experience and familiarity with collaborative development practices, including pull requests, code reviews, GitFlow, or trunk-based development.
• Experience with cloud computing, preferably GCP; experience with AWS or Azure is also acceptable.
• Knowledge of ETL/ELT tools and data integration patterns.
• Strong engineering mindset around automated testing, version control, reproducible deployments, and maintainable code.
• Familiarity with Terraform and Infrastructure as Code is a strong plus.
• Experience with dbt Fusion or migration toward dbt Core 2.0 is desirable.
• Knowledge of Airflow or Dagster, Kubernetes, and Docker is considered an advantage.
• Familiarity with data observability tools and practices, including dbt docs, Elementary, Monte Carlo, or OpenLineage, is a plus.
• Experience with sensitive-data masking, LGPD, compliance, and data-security practices is desirable.
• Knowledge of Kimball dimensional modeling, star schemas, or Data Vault is an advantage.
• Strong collaboration, communication, mentoring, and technical leadership skills.
• Comfortable working in agile, collaborative environments and taking ownership of complex technical initiatives.

Benefits

• 100% remote work.
• Porto Seguro medical insurance, with the possibility of including spouse and children.
• Porto Seguro dental insurance for employees and dependents.
• Profit Sharing (PLR).
• Childcare allowance.
• Alelo meal and food allowance.
• Home office allowance.
• Partnerships with educational institutions, including discounts and incentives for courses and degrees.
• Certification incentives, including cloud certifications in GCP, Azure, AWS, and other technologies.
• Livelo points program.
• TotalPass fitness and wellness benefit, with options for employees and family members.
• Mindself program focused on meditation, mindfulness, and quality of life.
• Collaborative environment with opportunities for technical growth, learning, and knowledge sharing.