Docket

Data Engineer

• Develop, deploy, and operate data pipelines to make data available for internal and external clients using AWS cloud infrastructure.
• Produce reports and dashboards using Metabase or other data visualization tools.
• Develop and support ETLs using Airflow, PySpark, and SQL.
• Monitor and respond to failures in data infrastructure processes.
• Manage S3 data lake using abstractions such as Iceberg or Delta Table.
• Gather requirements and create data models for the data warehouse.
• Implement performance monitoring and alerting solutions.
• Automate processes via scripts and code.
• Document deployed solutions.

Business Analyst

• Interface with Brazilian public agencies to request and obtain documentation;
• Work daily with various types of forensic and notarial/registry documents;
• Retrieve, issue, and manage documents requested by clients;
• Manage requests and deadlines, effectively managing time and workload;
• Ensure document delivery SLAs are met;
• Ensure agreed productivity targets are met;
• Ensure the quality of delivered documents;
• Ensure that all documents under your responsibility are actively being processed with the relevant agencies;
• Communicate with the customer service/support team;
• Accurately record payments and request reversals/refunds when necessary.

Junior Business Analyst

Product Designer

• Deeply understand the business rules, operating model, and regulatory context of Docket’s products.
• Understand product metrics, success indicators, and the company’s strategic objectives.
• Engage with internal and external stakeholders to align priorities and identify opportunities.
• Actively participate in shaping the product roadmap and strategic direction.
• Translate complex business problems into design and product hypotheses and opportunities.
• Propose viable, scalable approaches to achieve the company’s strategic goals.
• Plan and conduct qualitative and ethnographic research with users and customers.
• Plan and execute quantitative research to validate hypotheses and identify behavior patterns.
• Work closely with PMs and engineers using Continuous Discovery practices.
• Map user journeys, service flows, and operational processes.
• Identify pain points, needs, and opportunities to improve current experiences.
• Conduct usability tests and experiments to validate solutions before implementation.
• Use product analytics and behavioral analysis tools, such as Mixpanel and Hotjar, to analyze usage patterns, identify experience bottlenecks and journey friction, validate design hypotheses, and support data-driven decisions.
• Create and iterate on navigation flows, wireframes, and high-fidelity prototypes.
• Design experiences focused on operational efficiency, clarity, and trust.
• Ensure high usability and user experience quality.
• Collaborate with engineering on the implementation of design solutions.
• Contribute to the evolution of Docket’s Design System.
• Prioritize solutions that balance user experience, technical feasibility, and business impact.
• Map and design end-to-end services, considering not only the digital interface but also the processes, integrations, and operations involved.
• Build service blueprints that connect user experience with internal processes and systems.
• Identify operational bottlenecks and automation opportunities along the journey.
• Design experiences that integrate interfaces, APIs, documents, and operational flows.
• Work on the continuous improvement of the complete end-to-end customer experience.

Senior Product Designer

Machine Learning Engineer

• Assess and select appropriate technologies and tools.
• Coordinate planning and execution of team tasks.
• Participate in strategic meetings and alignments.
• Perform code reviews and ensure software quality.
• Resolve technical problems and roadblocks.
• Guide the team in difficult decisions.
• Align different company areas to ensure the intended outcomes.
• Actively participate in strategic discussions with product teams.
• Write code to help the team deliver, eliminate bottlenecks, and demonstrate standards for the project team to understand requirements and communicate test results effectively.
• Project Leadership: Lead machine learning teams and projects, setting goals, deadlines, and execution strategies.
• Mentorship and Guidance: Coach and train machine learning engineers, sharing knowledge and best practices.
• ML Strategy Definition: Develop machine learning strategies to address complex business problems and define success metrics.
• Performance Optimization: Optimize model performance through hyperparameter tuning, grid search, and other advanced techniques.
• Data Exploration: Perform exploratory data analysis (EDA) to discover insights and identify features important for models.
• Model Deployment to Production: Deploy models to production environments, ensuring scalability and maintainability.
• Research and Development: Keep up with recent research in machine learning and contribute to the development of new algorithms and techniques.
• Develop, train, and optimize Transformer- and LLM-based models for text processing tasks;
• Build robust pipelines for text pre-processing and post-processing;
• Apply software engineering best practices in Machine Learning projects;
• Work with structured and unstructured data, integrating models with databases and APIs;
• Participate in technical decisions about architecture, model versioning, testing, and deployment;
• Collaborate with data engineers and other teams to scale solutions in production.

Tech Lead – Machine Learning

• Develop, train, and optimize Transformer-based models and LLMs for text processing tasks;
• Build robust text preprocessing and postprocessing pipelines;
• Apply software engineering best practices in Machine Learning projects;
• Work with structured and unstructured data, integrating models with databases and APIs;
• Contribute to technical decisions on architecture, model versioning, testing, and deployment;
• Collaborate with data engineers and other teams to scale solutions in production.

Senior Machine Learning Engineer

Backend Engineer

• Participar diretamente da definição de arquitetura e do design de código;
• Seja responsável pelo desenvolvimento de aplicações Backend, escrevendo código de fácil manutenção e reutilizável (Código limpo e seguro) - Qualidade;
• Dar suporte para outros desenvolvedores do Time;
• Utilização avançada e correta do Spring Boot e seus módulos: (Ex: Spring Data, Spring Security, Spring Web);
• Desenvolvimento correto de API Rest, utilizando Spring Boot (Domínio completo dos verbos http e códigos de retorno http);
• Excelente conhecimento de Bancos de Dados Relacionais, tecnologias SQL e ORM (JPA2, Hibernate, JDBC Template) - Banco de Dados Postgres;
• Desenvolvimento orientado a testes;
• Identificar bugs, gargalos e outros problemas dentro do código, e conceber formas de resolver e/ou melhorar - (Segurança e Performance);
• Analisar os riscos e impactos no desenvolvimento de Feature ou manutenção nos sistemas;

Engenheiro Backend Sênior – Java, Spring Boot

Frontend Engineer

• Collaborate with the product team to prioritize and evaluate requests.
• Support architecture definition and resolve technical bottlenecks.
• Develop enterprise (SaaS web) applications using React or Next.js.
• Deliver pixel-perfect implementations (experience with Figma).
• Build scalable web platforms with a focus on security and performance.
• Ensure best practices in front-end application development.