Compass

Data Analyst

• Data Analysis: collect, process, and analyze large volumes of data to identify patterns, trends, and metrics (e.g., categorization, frequency);
• Cross-functional collaboration: work closely with product and business teams to ensure full alignment on analyses;
• Prioritization and requirements: prioritize the analytics pipeline, align with stakeholders across functions, and communicate specific needs to technical teams;
• Development of advanced analyses: apply more advanced statistical methods, such as clustering and probability distributions;
• Reporting and insights: prepare reports, dashboards, and presentations with actionable insights to support business decision-making;

Senior Data Analyst

Content Writer

• Create and revise microcopy, conversational flows, and transactional messages;
• Develop and maintain language guidelines and communication standards;
• Collaborate with UX, Product, Marketing, Customer Success, Sales, and Operations teams;
• Ensure consistency of tone of voice, language, and brand identity across all touchpoints;
• Map customer journeys and identify friction points, proposing content improvements guided by Customer Experience metrics;
• Create content for customer onboarding, support, retention, and proactive communications;
• Use data, research, and testing to validate hypotheses and optimize the customer experience;
• Conduct user research to inform content decisions.

UX Writer – Mid

• Lead and oversee end-to-end data projects, from refinement/discovery through testing/acceptance (UAT) and go-live;
• Organize and lead meetings with technical and business teams to gather and detail requirements;
• Prepare and maintain technical and functional documentation in collaboration with the involved areas;
• Act as the technical focal point for the project, serving as the intermediary between different areas (development, architecture, security, integration, QA, networking, and business);
• Route requests to the technical team responsible for development (vendors and internal teams);
• Monitor delivery progress to ensure the project advances as planned;
• Identify and act to remove impediments, facilitating unblockings with the areas involved;
• Oversee testing phases, acceptance (UAT), and production deployment;
• Discuss technical solutions with architects and specialized teams to ensure alignment with the current architecture;
• Support technical validations when necessary, including database queries;
• Monitor the progress of initiatives and maintain clear communication with stakeholders;
• Ensure organization, traceability, and smooth flow of requests related to data projects.

Databricks Data Analyst – Lead

• Lead and manage end-to-end data projects, from refinement/discovery through testing, acceptance (UAT) and go-live;
• Organize and facilitate meetings with technical and business teams to gather and detail requirements;
• Create and maintain technical and functional documentation in collaboration with the teams involved;
• Serve as the technical focal point for the project, acting as the liaison between different areas (development, architecture, security, integration, QA, networking and business);
• Assign and direct requests to the technical team responsible for development (vendors and internal teams);
• Monitor delivery progress to ensure the project advances according to plan;
• Identify and help remove impediments, driving unblockings across the involved areas;
• Oversee testing phases, UAT/acceptance and production deployment;
• Discuss technical solutions with architects and specialized teams, ensuring alignment with the existing architecture;
• Support technical validations when required, including database queries;
• Monitor the progress of initiatives and maintain clear communication with stakeholders;
• Ensure organization, traceability and smooth flow of requests related to data projects.

GCP Data Analyst – Lead

Project Manager

• Manage the Digital Asset Management (DAM) platform, ensuring organization, governance and standardization of digital assets;
• Define and maintain taxonomy, metadata, tags, categories and attributes, ensuring consistency and ease of searchability;
• Create and enforce governance policies, access controls, security and asset lifecycle management;
• Configure and optimize upload, approval and publishing workflows, aligning them with brand guidelines;
• Map current processes and propose improvements to reduce rework and increase efficiency;
• Validate platform functionality before implementation and monitor bug fixes;
• Document processes, policies and best practices to ensure standardization and scalability;
• Train users and teams on platform usage, creating support materials such as guides and tutorials;
• Act as a liaison between Marketing, IT and business areas, ensuring alignment with the brand’s needs;
• Ensure the quality, integrity and compliance of digital assets with defined standards.

Project Analyst – Mid

Data Scientist

• Desenvolver, treinar, validar e implantar modelos de Machine Learning e Deep Learning;
• Estruturar e manter pipelines de ETL/ELT integrando múltiplas fontes de dados (bases relacionais, APIs, arquivos, sistemas legados, etc.);
• Atuar na modelagem, extração e manipulação de dados utilizando Python e SQL;
• Trabalhar com bancos de dados Oracle, garantindo performance e integridade das informações;
• Implementar soluções em ambientes cloud (AWS / Azure);
• Aplicar técnicas de Processamento de Linguagem Natural (NLP), como tokenização, POS tagging, análise sintática e extração de entidades;
• Contribuir com práticas de MLOps (versionamento, automação de deploy, monitoramento de modelos, CI/CD para ML);
• Validar performance de sistemas RAG;
• Apoiar na definição de arquitetura de dados e boas práticas de engenharia.

Senior Data Scientist, Azure / AWS

DevOps Engineer

• Identify, plan, and implement improvements in production environments;
• Propose and implement technical and process improvements that add business value;
• Work on environment automation to promote operational efficiency;
• Enable and evolve the environment with a focus on standardization and DevOps best practices;
• Maintain a proactive approach to learning and experimenting with new technologies.

DevOps Engineer, AWS

• Identify, plan, and implement improvements in production environments;
• Propose and implement technical and process improvements that add business value;
• Work on environment automation to promote operational efficiency;
• Enable and evolve the environment with a focus on standardization and DevOps best practices;
• Maintain a proactive attitude toward learning and experimenting with new technologies.

Senior DevOps Engineer, AWS

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Senior Azure Data Engineer

• Develop, publish and maintain dashboards and reports in Power BI;
• Create and optimize data models for analysis and visualization;
• Write queries and analysis routines using SQL;
• Develop advanced measures and calculations with DAX;
• Work with Data Lake structures, organizing and consuming data from multiple sources;
• Use cloud services for data storage and data processing;
• Ensure the quality, consistency and reliability of information;
• Translate business needs into clear analyses and indicators (KPIs);
• Support clinical and administrative areas with data-driven insights;

Data Analyst – Mid-level, Hybrid, São Paulo

• Plan, organize, and facilitate operational ceremonies and routines (dailies, checkpoints, tactical alignments, and follow-up rituals).
• Monitor the progress of deliverables, managing risks, dependencies, and the availability of project artifacts.
• Ensure schedule control, predictability, and visibility of project activities and milestones.
• Act proactively to identify and remove impediments, serving as the link between the technical team and the client.
• Consolidate information for status reports, performance indicators, and project documentation.
• Monitor and ensure compliance with project prerequisites (access, artifact freezes, client validations).
• Communicate with internal and external stakeholders, aligning expectations to keep the project (Discovery) on schedule.
• Work strongly at the operational level, focusing on meeting deadlines and the schedule, reporting directly to the Delivery Manager.

• Work on migrating data pipelines from GCP and on-premises to AWS;
• Modernize the data architecture using AWS managed services;
• Ensure data governance, security, and adherence to global data standards;
• Optimize performance, costs, and reliability of the pipelines;
• Support the migration of BI workloads and regulatory data (RECOF‑SPED);
• Collaborate with local and global technical and business teams.

AWS Data Engineer – Specialist

• Design, define, and implement the data platform on Google Cloud Platform (GCP);
• Create, evolve, and optimize cloud data warehouses using BigQuery;
• Design and implement scalable, high-performance data architectures;
• Develop data processing pipelines using batch and streaming models;
• Orchestrate data workflows and integrations using Apache Airflow;
• Manage structured, semi-structured, and unstructured data, ensuring data quality, security, and governance;
• Implement integrations with APIs and Business Intelligence (BI) tools;
• Define best practices for data modeling, standardization, and data governance;
• Work collaboratively with technical teams and business stakeholders to define data-driven solutions;
• Ensure operational efficiency, reliability, and scalability of the data platform.

Senior GCP Data Architect

• Create, maintain, and improve CI/CD pipelines in GitLab (intermediate/advanced level);
• Manage code versioning with Git, supporting multiple teams and repositories;
• Provision and manage AWS infrastructure using Terraform, focusing on: creation and maintenance of reusable modules; configuration and management of AWS providers;
• Ensure cloud environments are secure, scalable, and well-governed;
• Support workloads for APIs, microservices, and AI solutions;
• Implement monitoring, logging, and observability practices;
• Work closely with Architecture and Development teams to standardize and evolve environments.

Senior AWS DevOps Engineer

• Work in Data Engineering;
• Gather requirements and design project solutions;
• Develop solutions that optimize data processes and data solutions;
• Apply ETL techniques using Databricks;
• Perform data modeling;