Sobre

• 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.
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• 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.

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How Jobgether works

• We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
• We appreciate your interest and wish you the best!
• Why Apply Through Jobgether?
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