Dadoteca

Data Engineer

• Maintain and enhance data pipelines and solutions
• Modernize processes and workflows currently supported by legacy technologies
• Develop and optimize data processing and transformation routines
• Design data structures using dimensional modeling
• Identify opportunities to improve data performance, quality, and governance
• Collaborate with cross-functional teams to define and implement technical solutions
• Ensure stability, reliability, and efficiency of data environments

Senior Data Engineer – Support

Product Manager

• Act as the product owner, defining the product vision, strategy and roadmap together with internal stakeholders, clients and business areas.
• Prioritize and manage the product backlog, aligning business demands, user needs, technical feasibility and value generation.
• Specify functional and technical requirements for digital products, health applications, data platforms, AI solutions, automation and analytics.
• Work closely with development, UX, QA, data, data engineering, data science and AI teams, ensuring deliveries meet acceptance criteria.
• Contribute to the design and evolution of products that use LLMs, Machine Learning models, analytics, BI, APIs, cloud services and intelligent automations.
• Perform acceptance testing, user validations, metrics monitoring and product performance analysis.
• Support discovery processes, user journey mapping, identification of pain points and definition of digital solutions focused on experience, usability and business impact.
• Ensure continuous delivery of value with a focus on the customer, innovation, scalability, security and quality.
• Oversee the full product lifecycle, from conception, discovery and development to launch, adoption, metrics and post-launch improvements.
• Work on digital health projects, applications, management platforms, data products, AI applied to healthcare and decision-support solutions.

Product Owner – Digital Health, Data & AI Products

Architect

• Support the design and implementation of solution architectures based on Artificial Intelligence and Generative AI.
• Gather and translate business requirements into technical solutions using AI, automation and data analysis.
• Develop and implement solutions using LLMs, RAG (Retrieval-Augmented Generation), AI agents and integrations with enterprise systems.
• Build and expose AI models and services via APIs and microservices.
• Implement solutions on cloud AI platforms, ensuring performance, security and governance.
• Participate in the definition and implementation of data architectures for AI applications, including Data Lakes, Data Warehouses and vector databases.
• Support proofs of concept (PoCs), technical testing and evaluation of new technologies.
• Apply best practices in development, governance, security and responsible use of Artificial Intelligence.
• Collaborate with multidisciplinary data, development and business teams to ensure proper integration of solutions.
• Support monitoring, maintenance and continuous evolution of deployed solutions using MLOps practices.
• Produce technical documentation, architecture diagrams and functional and technical specifications.
• Participate in technical meetings with clients and stakeholders to understand requirements and present solutions.

Senior Data Engineer – Support

Product Owner – Digital Health, Data & AI Products

AI Architect – Mid-level