Especialista em engenharia de dados (Data Eng - Data Architecture)

This position is posted by Jobgether on behalf of a partner company. We are currently looking for an Especialista em engenharia de dados (Data Eng - Data Architecture) in Brazil.

This role offers the opportunity to work at the intersection of data engineering, machine learning operations, and scalable data architecture within a highly innovative and collaborative environment. You will be responsible for designing, building, and optimizing robust data and MLOps pipelines that support the full lifecycle of machine learning models in production. The position plays a key role in ensuring that data systems are reliable, secure, and efficient, while enabling teams to deploy and monitor models at scale. You will collaborate closely with multidisciplinary teams to define best practices, improve observability, and strengthen governance across data-driven systems. This is an excellent opportunity for a senior professional passionate about data platforms, automation, and AI-driven solutions in a remote-first and innovation-focused organization.

Accountabilities:

• Design, build, and maintain scalable MLOps pipelines supporting the full machine learning lifecycle, including training, deployment, and monitoring.
• Develop and optimize CI/CD pipelines tailored for machine learning workflows and data-driven applications.
• Implement monitoring, logging, and observability solutions to track model performance in production environments.
• Define and apply strategies to detect, diagnose, and mitigate model performance degradation over time.
• Ensure data security, governance, and compliance standards are maintained across production systems and ML workflows.
• Collaborate with cross-functional teams to document, standardize, and improve MLOps and data engineering processes.
• Support the integration of machine learning models into production systems using modern data architecture principles.
• Contribute to the evolution of scalable and automated data infrastructure supporting AI and analytics initiatives.

Requirements:

• Strong experience in MLOps, including automation, orchestration, and lifecycle management of machine learning models.
• Advanced knowledge of containerization and orchestration tools such as Docker and Kubernetes.
• Solid experience with cloud platforms, especially AWS, applied to data and machine learning workloads.
• Proficiency in Python for data engineering, automation, and ML operations tasks.
• Experience implementing monitoring, logging, and observability frameworks for production ML systems.
• Strong understanding of data governance, security, and compliance best practices.
• Experience working with CI/CD pipelines in data or machine learning environments.
• Familiarity with ML frameworks and MLOps tools such as MLflow, Kubeflow, or SageMaker Pipelines is highly desirable.
• Knowledge of infrastructure as code tools such as Terraform or CloudFormation is a plus.
• Experience optimizing performance of data pipelines or ML systems is considered an advantage.
• Exposure to generative AI projects or integration of advanced AI technologies is a plus.
• Strong collaboration, documentation, and communication skills in multidisciplinary teams.
• Active participation in technical communities, events, or knowledge sharing initiatives is valued.

Benefits:

• Fully remote work model with high flexibility and autonomy.
• Flexible working hours focused on results and work-life balance.
• Health and dental insurance plans.
• 24/7 telemedicine access and mental health support, including free online therapy.
• Extended maternity and paternity leave policies.
• Wellness benefits including fitness partnerships and well-being programs.
• Meal and food allowances, transportation support, and home office assistance.
• Education support and career development programs.
• Internal communities, guilds, and learning groups for continuous growth.
• Life insurance and financial benefits including profit-sharing programs.
• Additional family and lifestyle support benefits, including childcare assistance.

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?    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.     #LI-CL1