• Administrar, configurar e manter a infraestrutura de servidores Linux, garantindo estabilidade, segurança e desempenho; • Monitorar o ambiente utilizando ferramentas como Zabbix e Grafana, identificando e atuando em incidentes conforme os processos estabelecidos, garantindo resposta dentro dos prazos definidos; • Implementar automações utilizando Ansible e scripts em Python para otimizar tarefas recorrentes; • Realizar troubleshooting em serviços web, como Nginx, Apache, PHP-FPM e Varnish; • Realizar troubleshooting em aplicações; • Participar de atividades de mitigação de vulnerabilidades e auditorias de segurança; • Atuar na resolução de incidentes escalados por camadas anteriores (N1 e N2), garantindo suporte técnico eficiente, colaborando com outras áreas para mitigação de problemas e buscando a identificação e correção da causa raiz para evitar recorrências; • Contribuir para projetos de evolução da infraestrutura, incluindo migração de servidores e adoção de novas tecnologias.

• Lead the design and development of scalable fullstack applications using React (SPA) and Node.js. • Own and drive monolith-to-SPA migration strategies, including incremental decomposition, API design, and frontend re-architecture. • Define and enforce frontend and backend architecture, patterns, and best practices. • Act as technical lead for the fullstack domain: reviewing designs, mentoring engineers, and setting engineering standards. • Collaborate closely with product, DevOps, and platform teams to align application architecture with infrastructure constraints. • Design and maintain backend services and APIs (REST/GraphQL) with a focus on performance, reliability, and maintainability. • Improve application observability, performance, and resilience. • Participate in hiring, onboarding, and growing senior engineering talent. • Drive technical decision-making with a long-term platform mindset.

• Advise clients and media buying teams on channel event instrumentation requirements and user attribution, such as Meta’s Conversions API (CAPI), Google Enhanced Conversions, TikTok Events API, and other platform-specific integrations. • Validate and architect web and app analytics event pipelines in tools such as Google Tag Manager and Mobile Measurement Partners such as AppsFlyer, Adjust, or Branch. • Design, execute, and analyze matched-market (geo-lift) incrementality tests using tools such as Meta’s GeoLift library and other ML tooling within Jupyter notebooks. • Contribute to and support Marketing Mix Modeling (MMM) initiatives, including data preparation, model interpretation, and client-facing presentation of results. • Write data ingest pipelines and API integrations using Python running on the Google Cloud Platform (GCP). • Create BI dashboards and views using Looker. • Write data pipelines using SQL in Data Build Tool (dbt) on Google BigQuery. • Investigate data discrepancies and troubleshoot pipeline and reporting issues across web, app, and advertising platforms. • Integrate web, app, eCommerce (e.g., Shopify), and CRM (e.g., Salesforce) data with advertising channel audience and conversion APIs (e.g., Facebook CAPI, Google Enhanced Conversions). • Implement custom BI visualizations using HTML/CSS/JS + Vue. • Implement OAuth endpoints, web callbacks, and other API integrations supporting data and reporting integrations in Python.

• Advise clients and media buying teams on channel event instrumentation requirements and user attribution, such as Meta’s Conversions API (CAPI), Google Enhanced Conversions, TikTok Events API, and other platform-specific integrations. • Validate and architect web and app analytics event pipelines in tools such as Google Tag Manager and Mobile Measurement Partners such as AppsFlyer, Adjust, or Branch. • Design, execute, and analyze matched-market (geo-lift) incrementality tests using tools such as Meta’s GeoLift library and other ML tooling within Jupyter notebooks. • Contribute to and support Marketing Mix Modeling (MMM) initiatives, including data preparation, model interpretation, and client-facing presentation of results. • Write data ingest pipelines and API integrations using Python running on the Google Cloud Platform (GCP). • Create BI dashboards and views using Looker. • Write data pipelines using SQL in Data Build Tool (dbt) on Google BigQuery. • Investigate data discrepancies and troubleshoot pipeline and reporting issues across web, app, and advertising platforms. • Integrate web, app, eCommerce (e.g., Shopify), and CRM (e.g., Salesforce) data with advertising channel audience and conversion APIs (e.g., Facebook CAPI, Google Enhanced Conversions). • Implement custom BI visualizations using HTML/CSS/JS + Vue. • Implement OAuth endpoints, web callbacks, and other API integrations supporting data and reporting integrations in Python.