01046b01e4
Umfangreiche Erweiterung der Skill-Bibliothek: Neue Skills für Humanisierung (Englisch/PT-BR), Design-Validierung, AI-SEO und Coolify-Deployment inkl. Regelwerke, Presets, Pattern-Referenzen, Testfälle und Automatisierungsskripte. Zusätzliche Skills für Revenue-Centric Design, Pier Cloud, OKF, Lebenslauf- und LinkedIn-Optimierung sowie zahlreiche Referenzdateien, Checklisten und YAML/JSON/Markdown-Templates. Einführung einer vollständigen OpenWiki-Dokumentation mit Architektur-, Domain- und Workflow-Beschreibungen, zentralem Index und automatisierten Updates. Modularer Aufbau, restriktive Lizenzen und umfassende Qualitäts- und Evaluationsmechanismen für alle neuen Inhalte.
138 lines
5.7 KiB
Markdown
138 lines
5.7 KiB
Markdown
# Presets de Cargo & Formatos Canônicos
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> Referência para auditoria LinkedIn e currículo ATS. Cobre profissionais especializados em geral — não apenas dev.
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---
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## Presets de Cargo
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Cada preset contém: **label**, **role**, **keywords**, **headline_areas**, **headline_tech** (ferramentas/competências).
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### Tecnologia
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| Label | Headline Canônica |
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|---|---|
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| `backend-engineer` | Backend Engineer \| APIs, Microservices & Distributed Systems \| Python · Java · Go · PostgreSQL · AWS · Kubernetes |
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| `frontend-engineer` | Frontend Engineer \| Web Apps, UX Performance & Design Systems \| React · TypeScript · Next.js · CSS · Performance |
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| `fullstack-engineer` | Full Stack Engineer \| Product Engineering, APIs & Full Stack Delivery \| React · Node.js · TypeScript · PostgreSQL · AWS |
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| `data-engineer` | Data Engineer \| Data Platform, CDP & Reliability \| GCP · Airflow · BigQuery · Spark · Terraform · dbt |
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| `devops-engineer` | DevOps / SRE \| Cloud Infrastructure, Reliability & Platform Ops \| Kubernetes · Terraform · AWS · Docker · CI/CD |
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| `mobile-engineer` | Mobile Engineer \| Mobile Apps, Performance & Cross-Platform \| Kotlin · Swift · Flutter · React Native |
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| `staff-engineer` | Staff Software Engineer \| Platform Architecture, Scale & Technical Leadership \| System Design · Distributed Systems · Cloud |
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### Dados & Analytics
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| Label | Headline Canônica |
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| `data-scientist` | Data Scientist \| Machine Learning, Statistical Modeling & Business Intelligence \| Python · R · TensorFlow · SQL · Tableau |
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| `data-analyst` | Data Analyst \| Business Intelligence, Reporting & Data Visualization \| SQL · Power BI · Tableau · Excel · Python |
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| `analytics-engineer` | Analytics Engineer \| Data Modeling, Metrics & Self-Serve Analytics \| dbt · SQL · Looker · BigQuery · Snowflake |
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### Marketing & Growth
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| Label | Headline Canônica |
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|---|---|
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| `growth-marketer` | Growth Marketing Manager \| Acquisition, Retention & Experimentation \| Google Ads · Meta Ads · GA4 · HubSpot · A/B Testing |
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| `product-marketer` | Product Marketing Manager \| Positioning, Launch Strategy & Sales Enablement \| Messaging · Competitive Intel · Content · GTM |
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| `seo-specialist` | SEO Specialist \| Technical SEO, Content Strategy & Link Building \| Ahrefs · Screaming Frog · GSC · GA4 · Schema |
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### Finanças & Negócios
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| Label | Headline Canônica |
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| `financial-analyst` | Financial Analyst \| FP&A, Modeling & Strategic Planning \| Excel · Power BI · SAP · Bloomberg · SQL |
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| `product-manager` | Product Manager \| Discovery, Roadmap & Delivery \| Jira · Amplitude · Figma · SQL · OKRs |
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| `management-consultant` | Management Consultant \| Strategy, Operations & Digital Transformation \| McKinsey 7S · Lean · Excel · PowerPoint |
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### Engenharia & Indústria
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| Label | Headline Canônica |
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| `mechanical-engineer` | Mechanical Engineer \| Product Design, FEA & Manufacturing \| SolidWorks · AutoCAD · ANSYS · GD&T · Lean Manufacturing |
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| `civil-engineer` | Civil Engineer \| Structural Design, Project Management & BIM \| AutoCAD · Revit · SAP2000 · MS Project · BIM 360 |
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> **NOTA:** Estes são exemplos. O usuário pode definir qualquer cargo — o agente deve adaptar keywords e sugestões ao contexto fornecido.
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---
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## Formatos Canônicos
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### Headline LinkedIn
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**Formato:** `{Posição} | {Áreas de trabalho mais fortes} | {Ferramentas/Competências com ·}`
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**Regras:**
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- Exatamente 3 blocos separados por `|`
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- Bloco 1: cargo/posição (com senioridade quando relevante)
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- Bloco 2: áreas de domínio / especialidades
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- Bloco 3: ferramentas, tecnologias ou competências-chave separadas por `·`
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- Máximo 220 caracteres
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**Exemplo:**
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```
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Senior Data Engineer | Data Platform, CDP & Reliability | GCP · Airflow · BigQuery · Spark · Terraform
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```
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---
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### Bullet de Experiência (LinkedIn)
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**Formato:** `Ação + métrica em destaque + ferramentas/tecnologias + impacto para a empresa`
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**Regras:**
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- ~3 linhas máximo por bullet
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- Máximo 5 bullets por experiência
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- Iniciar com verbo de ação
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- Incluir pelo menos 1 métrica por bullet quando possível
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**Exemplo:**
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```
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Productionized a multi-agent AI remediation platform using Google ADK, FastAPI, LLMs, RAG,
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Kubernetes, and GitHub-hosted runbooks, resolving ~70% of recurring low-risk KTLO incidents
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across Airflow, Dataproc, BigQuery, and Keboola
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```
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---
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### About LinkedIn
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**Modelo narrativo:**
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1. Abertura com anos de experiência + foco principal
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2. Empresa atual com escala/métricas
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3. Áreas de atuação
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4. Experiência anterior com provas
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5. Lista de domínios/competências/stack no final
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**Tamanho:** 1000–2000 caracteres ideal
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**Exemplo:**
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```
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I'm a Senior Data Engineer and Cloud Data Architect with 6+ years of experience focused on
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helping create and support scalable, reliable, and governed data platforms across GCP and Azure.
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At ShopNova, I work on petabyte-scale data platforms supporting 2,000+ pipelines, 500+
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Airflow/Composer DAGs, and large-scale GCP workloads. [...]
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My strongest areas are Cloud Data Architecture, Data Engineering, Airflow/Composer, GCP, Azure,
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BigQuery, Dataproc, Databricks, PySpark, Terraform, Kubernetes, CDP, Observability, and AI
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Automation.
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```
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---
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### Bullet de Currículo (ATS)
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**Formato:** `Verbo de ação + resultado quantificado + contexto/ferramenta`
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**Regras:**
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- 1–2 linhas por bullet
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- 4–6 bullets por experiência
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- Priorizar impacto mensurável
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- Usar verbos de ação fortes (Projetou, Implementou, Reduziu, Automatizou, Liderou, Otimizou)
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**Exemplo:**
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```
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Reduziu tempo de processamento de pipelines em 40% ao migrar jobs Spark para Dataproc Serverless com Terraform
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Automatizou 200+ DAGs no Airflow/Composer, eliminando 15h/semana de intervenção manual
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```
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