ENGENHEIRO DE DADOS PLENO

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

This role offers the opportunity to build and support data foundations that power innovative AI and generative AI initiatives.

You will contribute to database architecture, data pipelines, integrations, and the processing of large and complex datasets.

The position combines hands-on data engineering with exposure to LLMs, AI agents, MLOps, and modern cloud technologies.

You will help ensure that data is reliable, accessible, and ready for data scientists and other stakeholders working on AI solutions.

The role also involves supporting AI experimentation, monitoring model performance, and identifying opportunities to improve user experiences.

You will work in a distributed, collaborative environment where knowledge sharing and continuous learning are strongly encouraged.

This fully remote opportunity is ideal for a mid-level data engineer who wants to deepen their expertise at the intersection of data engineering and AI.

Accountabilities:

As a Data Engineer, you will contribute to the architecture, development, and maintenance of data solutions supporting AI projects. You will work across data pipelines, integrations, cloud infrastructure, AI experimentation, monitoring, and documentation to help ensure that data and AI solutions are reliable and ready for business use.

• Support database architecture and design for AI-focused projects.
• Assist with the implementation and maintenance of data pipelines for ingesting, storing, and processing large volumes of data.
• Ensure data is available, accessible, reliable, and ready for use by data scientists and other project stakeholders.
• Develop and maintain data integrations between different systems and platforms.
• Support the use of structured, vector, and unstructured data sources within AI solutions.
• Assist with prototyping and testing generative AI models to address specific business challenges.
• Contribute to the development and evaluation of LLM, agent, and agentic AI solutions.
• Analyze logs, metrics, and model usage data to identify failures, unexpected behavior, and opportunities to improve user experience.
• Support the implementation of MLOps and AIOps practices, including model CI/CD, versioning, and monitoring.
• Participate in the design of business process solutions leveraging artificial intelligence.
• Document project processes, methodologies, technical approaches, and results clearly and accessibly.
• Collaborate with technical and business stakeholders to continuously improve data and AI solutions.
• Contribute to experimentation, testing, and continuous improvement across AI initiatives.

Requirements:

The ideal candidate has a strong foundation in data engineering and is interested in applying modern data and AI technologies to real-world business challenges. You should be comfortable working with large datasets, cloud platforms, programming languages, data pipelines, and emerging AI development frameworks.

• Professional experience with database architecture and data pipeline design.
• Knowledge of data integration between different systems and platforms.
• Experience working with structured, vector, and unstructured databases or data technologies.
• Strong programming skills in Python, PySpark, and SQL.
• Knowledge of cloud infrastructure and frameworks, including platforms such as AWS, Azure, GCP, Databricks, Dataiku, or Salesforce.
• Familiarity with LLM, AI agent, and agentic AI development stacks and frameworks.
• Knowledge of MLOps and AIOps architectures and practices.
• Understanding of CI/CD for machine learning models, model versioning, and monitoring tools such as MLflow.
• Familiarity with AI-assisted development tools and IDE-based solutions such as Cursor, GitHub Copilot, Claude Code, or Codex.
• Ability to investigate technical issues using logs, metrics, and other operational data.
• Strong analytical and problem-solving skills.
• Ability to collaborate effectively with technical and business stakeholders in a distributed environment.
• Databricks, Azure, or AWS certifications are a plus.
• Knowledge of SAS is a plus.
• Experience implementing machine learning or computer vision solutions within data pipelines is a plus.
• Knowledge of data governance is a plus.
• Experience optimizing infrastructure costs for AI projects through FinOps practices is a plus.
• Knowledge of Spec-Driven Development (SDDs) for AI projects is a plus.
• Willingness to work remotely from 8:00 AM to 5:00 PM.
• Candidates who do not meet every requirement are encouraged to apply, as profiles will be evaluated based on their overall qualifications and experience.

Benefits:

• Fully remote work model.
• Working hours from 8:00 AM to 5:00 PM.
• Environment focused on learning and professional growth.
• Performance evaluations and regular feedback to support continuous development.
• Food and/or meal allowance.
• Medical and dental insurance for employees and their families.
• Pharmacy partnerships offering discounts on medications.
• Childcare assistance according to company policy.
• SESC partnership providing access to cultural, leisure, and recreational activities.
• Discounts and partnerships for language, technology, and professional development courses.
• Payroll-deducted loan program with attractive rates and financial education support.
• Corporate University and learning paths covering technology, soft skills, market trends, and other topics.
• Employee referral program with potential rewards and bonuses.
• Collective life insurance.
• Inclusive and collaborative environment with opportunities to work alongside distributed teams.