A3Data

Data Engineer

• Design, develop, and maintain robust, scalable data architectures in cloud or hybrid environments, aligned with clients' business needs.
• Build and optimize data pipelines (batch and streaming), ensuring reliable ingestion, processing, and delivery of information.
• Work with large volumes of data from multiple sources, focusing on solving business problems.
• Model data for analytical, predictive, and prescriptive consumption, supporting data science teams and business stakeholders.
• Ensure data security, governance, and quality, complying with internal policies and regulatory requirements such as LGPD (Brazilian Data Protection Law).
• Identify opportunities for continuous improvement in data flows, promoting efficiency, cost reduction, and increased reliability.
• Serve as a technical reference for the team and the client, supporting architectural decisions, providing technical mentorship, and promoting best practices.

Senior Data Engineer

Machine Learning Engineer

• Define and implement scalable, reproducible, monitorable, production-ready Machine Learning architectures.
• Develop, evolve, and maintain production Machine Learning pipelines and services, ensuring reliability and performance.
• Deploy highly available models and pipelines with a focus on MLOps, CI/CD, and automation.
• Collaborate with data scientists, data engineers, developers, and business stakeholders.
• Diagnose and resolve complex issues related to models and pipelines in production.
• Lead technical discussions and workshops, and support architectural decisions with teams and clients.
• Contribute to raising the client's and A3 Data's technical maturity by promoting best practices.

Senior Machine Learning Engineer

• Develop, train, and improve Machine Learning models, ensuring reproducibility, scalability, and production monitoring;
• Implement and manage the model lifecycle, with versioning for code, data, metrics, and artifacts, following MLOps best practices;
• Package models as scalable, highly available services integrated into automated pipelines;
• Support and continuously improve ML solutions in production, identifying and fixing issues;
• Collaborate with Data Engineering, Data Science, and business teams in a multidisciplinary environment;
• Perform code reviews and support the technical development of more junior engineers;
• Participate in technical discussions with clients, explaining solutions, architectural decisions, and trade-offs.

Machine Learning Engineer – Mid-level

Data Scientist

• Lead end-to-end Data Science projects using agile methodologies with a strong focus on delivering business value.
• Perform exploratory data analysis (EDA), identify patterns and trends, and generate actionable insights to support decision-making.
• Develop, evaluate, and implement statistical, predictive, and prescriptive models (both supervised and unsupervised).
• Act in a consultative manner to understand client pain points and needs throughout the project.
• Present results, analyses, and recommendations to technical and non-technical stakeholders with clarity and storytelling.
• Actively collaborate with the team, sharing knowledge, best practices, and new technical approaches.
• Support internal requests and strategic initiatives as needed.

Mid-level Data Scientist

• Lead end-to-end Data Science projects using agile methodologies with a focus on delivering business value.
• Perform exploratory analyses to identify patterns, trends and generate actionable insights to support decision-making.
• Develop, evaluate and implement statistical, predictive and prescriptive models (supervised and unsupervised).
• Act in a consultative manner to understand client pain points and needs throughout the project.
• Present results, analyses and recommendations to technical and non-technical stakeholders with clarity and storytelling.
• Collaborate actively with the team, sharing knowledge, best practices and new technical approaches.
• Support internal requests and strategic initiatives when needed.

Data Engineer – Mid-level

• Develop and evolve Data Science and Generative AI solutions, with a focus on LLMs, applying approaches such as prompt engineering, RAG (Retrieval-Augmented Generation), and fine-tuning when necessary;
• Design and implement end-to-end data pipelines, from ingestion to making data available for consumption;
• Work with AWS (especially AWS Bedrock) and Databricks, ensuring scalability, performance, and governance;
• Build, version, and expose models via APIs (FastAPI), with attention to security and observability;
• Collaborate with data engineering, DevOps, and client stakeholders;
• Participate in meetings, technical alignments, and presentations, explaining solutions clearly and objectively;
• Ensure best practices for CI/CD, code versioning, and automation across the model lifecycle;
• Support technical decisions considering cost, performance, risks, and business value.

Senior Data Scientist

Frontend Engineer

• Develop and evolve web applications in React and mobile applications in React Native, ensuring high technical quality and excellent user experience.
• Work end-to-end on building rich, accessible, high-performance, and scalable interfaces.
• Collaborate with Product, Design (UX/UI), and Back-End teams to turn business requirements into efficient technical solutions.
• Define and apply front-end architecture patterns and engineering best practices.
• Ensure visual and technical consistency through design systems and component libraries.
• Optimize application performance, accessibility, and usability.
• Integrate front-end applications with REST and GraphQL APIs.
• Implement and maintain automated tests (unit, integration, and end-to-end).
• Actively participate in code reviews, promoting quality and continuous team improvement.
• Investigate and resolve bugs and production incidents.
• Mentor more junior developers and disseminate front-end best practices.
• Contribute to improvements in processes, tools, and development workflows.

Senior Front-End Developer

Backend Engineer

• Develop, evolve and maintain back-end applications in Java 17+ using Spring Boot
• Design and implement REST APIs (and occasionally GraphQL), ensuring best practices in design, security and performance
• Actively participate in technical refinement of requirements together with product and architecture teams
• Contribute to system architecture decisions, especially in microservices environments
• Implement and maintain integrations between internal and external systems
• Ensure code quality through automated tests, code reviews and engineering standards
• Evolve and maintain relational databases, modeling data efficiently
• Support observability, monitoring and production incident resolution
• Collaborate with the team on CI/CD, automation and cloud initiatives
• Mentor less experienced developers and promote best practices within the team
• Contribute to continuous improvement of processes, application performance and reliability.