This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Mid Level AI Data Engineer based in Brazil.
This role is an opportunity to build reliable, scalable data products in an environment where AI is embedded directly into the software development lifecycle.
You will transform raw data into trusted, reusable products that support analytics, business decisions, and AI-powered agents.
The position combines modern data engineering, analytical modeling, governance, and AI-assisted development practices.
You will work with technologies such as Azure Databricks, ADF, Microsoft Fabric, Power BI, Python, and SQL.
You will also contribute to agent development, workflow orchestration, and integrations across repositories, pipelines, APIs, and development tools.
Success in this role means delivering high-quality, secure, observable, and well-documented data solutions that create consistent value for the business.
You will join a collaborative, innovation-driven environment focused on modern engineering practices and continuous improvement.
Accountabilities:
- Develop data transformations and analytical models using Azure Databricks, Azure Data Factory, Microsoft Fabric, and Power BI.
- Build and maintain Bronze, Silver, and Gold analytical layers, as well as business-oriented semantic models.
- Translate business requirements into scalable data models and establish, document, and standardize corporate metrics.
- Ensure data quality, testing, observability, governance, and documentation across data products and pipelines.
- Support the creation of datasets designed for Analytics applications and AI-powered agents.
- Apply AI throughout the software development lifecycle, including code generation, testing, refactoring, debugging, and development automation.
- Create structured specifications for spec-driven development and critically review AI-generated outputs for quality, consistency, and security.
- Build and orchestrate AI agents capable of multi-step workflows, tool usage, planning, and execution.
- Develop reusable AI skills and compose capabilities across different workflows and use cases.
- Integrate AI-driven workflows with repositories, pipelines, APIs, Git, CI/CD, issue-tracking, and observability tools.
- Contribute to multi-agent and human-agent workflow orchestration while promoting strong engineering, modeling, governance, and documentation practices.
Requirements:
- Advanced knowledge of SQL and solid experience with data modeling, data warehousing, and/or lakehouse architectures.
- Hands-on experience with Databricks and Python for data engineering and analytical workloads.
- Experience developing reliable data solutions with strong practices around quality, governance, testing, observability, and documentation.
- Proficiency with GitHub and modern version-control practices.
- Solid understanding of the complete software development lifecycle, from design and development through testing, deployment, and operations.
- Practical experience using AI extensively throughout development, including code generation, testing, refactoring, and debugging.
- Strong understanding of spec-driven development, using structured specifications as a primary input for AI-assisted engineering.
- Experience building AI agents involving multi-step execution, tool usage, planning, and orchestration.
- Knowledge of reusable AI skills, capability composition, and structured prompt-based operational interfaces such as slash commands.
- Experience with MCP (Model Context Protocol) or equivalent approaches for integrating AI systems with tools and data.
- Familiarity with workflow orchestration involving multiple agents and/or human-agent collaboration.
- Ability to critically evaluate AI-generated outputs with a focus on quality, security, consistency, and business requirements.
- Strong analytical thinking, attention to detail, collaboration skills, and the ability to work effectively in a modern, fast-paced engineering environment.
Benefits:
- Health and dental insurance.
- Meal and food allowances.
- Childcare assistance.
- Extended parental leave.
- Access to fitness, health, and wellness partnerships through Wellhub/TotalPass.
- Profit-sharing program (PLR).
- Life insurance.
- Continuous learning opportunities through an internal learning platform.
- Discount club and partner benefits.
- Free online platform focused on physical health, mental health, and overall well-being.
- Pregnancy and responsible-parenthood support programs.
- Partnerships with online learning platforms.
- Language-learning platform and development opportunities.
- Additional benefits and professional development initiatives.
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!
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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