[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] Candidate is an exceptionally strong technical architect with proven, hands-on experience designing and building complex, resilient systems from scratch, including self-hosted AI/LLM infrastructure. While he lacks direct experience in traditional core banking and specific Brazilian regulatory frameworks (Bacen), his deep background in transactional crypto systems, API integration, and rapid learning ability make him a high-potential fit for a strategic role. **✅ Strengths:** - Expertise in emerging technologies (AI/LLMs) - Proven ability to architect and build critical systems from scratch - Strong background in mission-critical API integration and automation **❌ Missing Required:** Conhecimento de requisitos regulatórios e compliance técnico em ambiente supervisionado pelo Bacen

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Pro] The candidate is a proven systems architect with a strong trajectory and demonstrated ability to build complex, automated systems from the ground up. However, there is a critical gap in the core required technology (Databricks) and a lack of the specified deep experience in AWS and PySpark, making it a weak match for this specialized role despite strong foundational skills. **⚠️ Critical Gaps:** - Databricks: The resume shows no experience with Databricks or equivalent Apache Spark platforms, which is a core requirement. **✅ Strengths:** - Demonstrated end-to-end system architecture from concept to production - Strong Python and SQL skills applied in real-world systems - Proven fast learner with a clear career progression into complex AI/Infrastructure roles **❌ Missing Required:** PySpark, Deep AWS Expertise (resume only lists 'AWS Basics'), 8+ years of data engineering/architecture experience (candidate has ~6 years of directly relevant experience)

[ANALYSIS_REPORT] **WEAK_MATCH** [Copilot: gpt-5] Strong systems/automation background (Docker/Terraform/Linux/Python/SSO) but lacks Oracle/OCI, public-sector pre-sales, cloud migration and DR fundamentals; fast-learner potential raises but critical gaps remain. **⚠️ Critical Gaps:** - Oracle Cloud Infrastructure (OCI) - Oracle Database (RAC/Data Guard) - Disaster Recovery (RTO/RPO/DR) - Cloud migration delivery - Public sector pre-sales domain experience **✅ Strengths:** - Infrastructure automation (Docker/Terraform/Linux) - Python/SQL engineering with clean architecture - Identity/Security fundamentals (OIDC/SAML, RBAC) **❌ Missing Required:** Pre-sales experience, Cloud migration planning and delivery, Servers/Storage/Backup solutions, Middleware, Replication solutions, RTO/RPO/DR concepts, Multi-Cloud experience, Networking/Connectivity for cloud (VPN/FastConnect), Data Center/Hosting architectures

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] Candidate is a strong conceptual match with proven, hands-on experience in self-hosted AI infrastructure and systems architecture, aligning perfectly with the core responsibilities. However, a critical gap exists in the required development stack (C#/.NET/Node/React vs. candidate's Python background), and they are missing experience with Kubernetes, which lowers the score. **⚠️ Critical Gaps:** - Development Stack: Required (C#, .NET Core, Node.js, React) vs. Candidate (Python) **✅ Strengths:** - Hands-on AI Infrastructure Experience (Self-hosted LLMs) - Strong Systems Architecture and Automation Skills (JIT System) - Proven Fast Learner with Clear Career Progression Towards AI **❌ Missing Required:** C#, .NET Core, Node.js, React, Kubernetes, MongoDB, TensorFlow, Azure AI, AWS SageMaker

[ANALYSIS_REPORT] **WEAK_MATCH** [Copilot: claude-sonnet-4.5] Candidate has strong fundamentals in Python, SQL, infrastructure automation, and systems architecture, but lacks the critical Azure-specific expertise required for this senior role. While the candidate demonstrates 'fast learner' potential with proven ability to build complex end-to-end systems (e-commerce automation, AI infrastructure), this position requires 5+ years of hands-on Microsoft Azure experience and deep expertise with Azure data services. The role is highly specialized in Azure ecosystem, not a general cloud/data engineering position where skills transfer easily. **⚠️ Critical Gaps:** - 5+ years Azure Cloud Platform experience (REQUIRED - candidate has 'AWS Basics' only) - Deep Microsoft Fabric experience (REQUIRED - not present) - Azure Databricks hands-on expertise (REQUIRED - not present) - PySpark for real-time pipelines (REQUIRED - candidate has PyTorch only) - Azure DevOps experience (REQUIRED - has generic CI/CD) **✅ Strengths:** - Strong Python and SQL foundation with production experience - Proven systems architect who builds end-to-end automated solutions (e-commerce platform demonstrates capability) - Infrastructure automation mindset with Docker, Terraform, and CI/CD experience transferable to Azure IaC **❌ Missing Required:** 5+ years as Data & Analytics Solution Architect, 5+ years working with Azure Cloud Platform, Deep and recent Microsoft Fabric experience, Azure Databricks production experience, PySpark for real-time, low-latency pipelines, Azure Data Factory, Data Lake, Stream Analytics hands-on, GraphQL API design within Azure, Azure DevOps expertise, Power BI for enterprise BI solutions, Azure security best practices (IAM, encryption, compliance)

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] The candidate is an exceptionally strong systems architect with proven experience in building complex, automated infrastructure from scratch. While they significantly exceed the general engineering and problem-solving requirements, there is a critical gap in the specified technology stack. The role requires a Subject Matter Expert in the Microsoft/Azure ecosystem, where the candidate has no demonstrated experience. **⚠️ Critical Gaps:** - Role requires deep Microsoft/Azure expertise, candidate has none **✅ Strengths:** - Deep systems architecture and automation skills - Proven fast learner with a strong career trajectory toward AI/Infrastructure - Experience building production systems with a focus on business ROI **❌ Missing Required:** Azure AZ-104, Azure AZ-900

[ANALYSIS_REPORT] **WEAK_MATCH** [Copilot: gpt-4.1] The candidate demonstrates strong architecture, automation, and integration skills, with a proven record in complex systems and business process optimization. However, there is no direct SAP experience, nor evidence of SAP-specific tools, modules, or methodologies required for this senior role. The candidate's fast learning and systems background are strengths, but the absence of SAP domain expertise is a critical gap. **⚠️ Critical Gaps:** - No SAP project experience - No SAP module or tool proficiency - No architecture governance in SAP context **✅ Strengths:** - Complex systems architecture - Process automation and optimization - Fast learner with cross-domain experience **❌ Missing Required:** 12+ years SAP solutions experience, SAP S/4HANA, SAP Business Technology Platform, SAP Cloud, SAP module expertise (FI, CO, SD, MM), SAP-specific fit-gap and configuration tools

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] Candidate is an exceptionally strong fit, demonstrating a clear career trajectory toward systems architecture and AI infrastructure. Extensive experience in designing and building complex, automated systems from the ground up (JIT inventory, LLM clusters) strongly suggests the capability to master the AWS platform, despite direct AWS experience being listed as basic. Proven fast learner with a C2 English certification. **✅ Strengths:** - Proven Systems Architecture Experience - Strong Self-Taught/Fast-Learner Profile - Clear Career Progression Towards AI/Infra Roles

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] The candidate is an exceptionally strong technical fit, with demonstrated hands-on experience building both Generative AI (self-hosted LLMs) and agentic systems (automated JIT inventory, trading bots). The primary gaps are the lack of public-facing thought leadership and explicit experience with human-in-the-loop workflows, which are stated requirements. **⚠️ Critical Gaps:** - Willingness to relocate to Guatemala is unconfirmed and mandatory. **✅ Strengths:** - Deep, hands-on experience with self-hosted LLMs and AI infrastructure. - Proven ability to architect and build complex, autonomous 'agentic' systems for real-world business problems. - Strong career trajectory demonstrating a deliberate progression into AI systems architecture. **❌ Missing Required:** Evidence of thought leadership (blogs, talks, videos), Experience designing human-in-the-loop systems

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Pro] The candidate is a strong systems architect with proven "metal-up" AI infrastructure and automation skills, meeting the 10-year experience mark. However, there are significant gaps in core data architecture domains required for this Principal role, particularly in Big Data technologies (Spark/Streaming), Data Governance, and BI visualization. While they possess deep, hands-on GenAI knowledge, it's self-hosted and lacks the required proficiency in specific AWS services like Sagemaker, Bedrock, and the broader AWS data ecosystem. **⚠️ Critical Gaps:** - Big data processing using Spark, Streaming solutions, and NoSQL **✅ Strengths:** - End-to-end system architecture and automation (JIT system) - Deep, practical experience with GenAI/LLMs from the infrastructure level - Proficient in DataOps tooling (Terraform for IaC, CI/CD, Python) **❌ Missing Required:** At least 4 years of experience in AWS data landscape, BI dashboards and visualizations, Data Governance and MDM, Proficiency in Sagemaker, Proficiency in Bedrock

[ANALYSIS_REPORT] **DISQUALIFIED** [G2.5 Pro] The candidate is a strong hands-on technical architect but lacks the crucial pre-sales and client-facing proposal generation experience required for this role. While his AI and systems-building skills are impressive, the job's core function is sales engineering, which represents a significant career pivot. Furthermore, the candidate does not meet the mandatory location requirement, leading to disqualification. **⚠️ Critical Gaps:** - Experiência em pré-vendas (o cargo é para criar propostas para novos clientes, não para desenvolvimento interno) - Requisito de localização (residência em Campinas ou região) **✅ Strengths:** - Profunda experiência prática com infraestrutura de IA (LLMs auto-hospedados) - Histórico comprovado em arquitetar e construir sistemas de produção complexos do zero - Rápida capacidade de aprendizagem e aplicação de tecnologias emergentes **❌ Missing Required:** Experiência comprovada em elaboração de propostas técnicas para clientes, Habilidades de negociação e persuasão, Dimensionamento de equipes em contexto de venda

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: gpt-4.1] The candidate demonstrates strong experience in architecture, integration, automation, and cloud fundamentals, with deep skills in Python, Linux, Docker, Terraform, and system design. There is clear evidence of fast learning, hands-on leadership, and end-to-end delivery of complex systems, including automation and integration. However, there are some missing or weakly evidenced skills in middleware (ESB, message brokers), Kubernetes/OpenShift, advanced cloud (beyond basics), and specific financial/banking platform integration. **⚠️ Critical Gaps:** - Kubernetes/OpenShift (core for modern platform orchestration) - ESB/Message Brokers (key for banking integrations) **✅ Strengths:** - Python and automation expertise - System architecture and integration - Cloud and infrastructure fundamentals **❌ Missing Required:** Kubernetes, OpenShift, ESB, Message Brokers

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Pro] O candidato é um engenheiro de infraestrutura e IA tecnicamente muito forte, com experiência comprovada em automação e implementação de LLMs. No entanto, existe uma lacuna crítica na experiência de pré-vendas consultivas, que é o foco principal da função. Além disso, falta conhecimento em plataformas de dados modernas (Databricks, Snowflake) e nuvens múltiplas (Azure, GCP) exigidas. **⚠️ Critical Gaps:** - Experiência em pré-vendas técnicas ou consultoria de clientes **✅ Strengths:** - Forte experiência prática ('Hand's On') em IA e LLMs - Habilidade comprovada em automação de sistemas complexos - Capacidade de traduzir requisitos de negócio em arquitetura técnica **❌ Missing Required:** Conhecimento Sólido em Plataforma de dados: Databricks, Fabric, BigQuery, Snowflake, Conhecimento Sólido em cloud computing - Azure, GCP, Experiência com BI ou Power Platform

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: claude-sonnet-4.5] Strong foundational match with proven system architecture experience and automation expertise. Candidate demonstrates end-to-end solution design capability (JIT inventory system, AI infrastructure) and business-to-tech translation skills. Primary gaps are in enterprise-scale cloud orchestration (Kubernetes), messaging systems (Kafka/RabbitMQ), and formal architecture frameworks (TOGAF). However, the 'Fast Learner' profile is evident: self-hosted LLM clusters, infrastructure automation, and successful complex system delivery indicate strong adaptability. The Supply Chain + Finance background aligns well with FinOps and business-oriented architecture thinking. **✅ Strengths:** - End-to-end system architecture: Proven ability to design and deliver production systems from concept to execution (95%+ uptime JIT inventory system) - Business-to-tech translation: Unique blend of Supply Chain/Finance domain expertise with technical implementation (aligns perfectly with stakeholder communication requirement) - Modern infrastructure automation: Hands-on Docker, Terraform, Python automation, and self-hosted AI clusters demonstrate contemporary tech stack alignment **❌ Missing Required:** Kubernetes (container orchestration), Azure platform experience, Google Cloud platform experience, Kafka/RabbitMQ (messaging/event streaming), Corporate network infrastructure (VPN, DNS, load balancing), Ansible automation, Jenkins/GitLab CI/CD pipelines

[ANALYSIS_REPORT] **WEAK_MATCH** [Copilot: gpt-5-mini] Strong systems-architecture and Python automation background, proven delivery of production systems and self-hosted hardware stacks indicates high fast-learning potential; however the role requires substantial C/C++ and embedded test-framework experience which are not evident on the resume. **⚠️ Critical Gaps:** - C/C++ production experience in high-tech/embedded domain (blocking for a lead Test Architect role specifying 7+ years with these languages) - Hands-on embedded/hardware-level test qualification (PCB/FPGA/SoC) and test frameworks **✅ Strengths:** - Python-first automation and scripting experience - Systems architecture + production deployment (metal-up / self-hosted clusters) - Demonstrated autonomy, rapid learning and leadership (Founder / Head of Engineering) **❌ Missing Required:** 7+ years demonstrable experience with C/C++ in high-tech/embedded systems, Demonstrable experience defining/operationalizing test architecture specifically for embedded qualification (tools + processes)

[ANALYSIS_REPORT] **POOR_FIT** [Copilot: claude-sonnet-4.5] Significant technology stack mismatch. The role requires deep Oracle ecosystem expertise (Oracle Visual Builder, Oracle ADF, PL/SQL) and enterprise Java frameworks (Spring Boot, Spring Framework), plus React.js frontend development. The candidate demonstrates strong systems architecture thinking, Python automation, and infrastructure skills, but lacks the specific Oracle/Java enterprise stack that forms the core of this position. The candidate's background in Supply Chain and Finance provides domain transferability, but the technical gap is substantial. **⚠️ Critical Gaps:** - Oracle technology stack (Oracle Visual Builder, Oracle ADF) - BLOCKING - Spring Boot/Spring Framework enterprise Java development - BLOCKING - React.js frontend development - BLOCKING - PL/SQL database programming - BLOCKING **✅ Strengths:** - Strong systems architecture and integration experience - Financial services domain background (Financial Analyst, algorithmic trading) - SQL and database fundamentals (transferable to PL/SQL with learning) **❌ Missing Required:** React.js experience, Oracle Visual Builder, Oracle ADF architecture, Spring Boot, Spring Framework, PL/SQL, Asset & Wealth Management domain expertise

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: gpt-5-mini] Strong infrastructure automation, on‑prem AI/LLM hosting and DevOps foundations with proven systems architecture and fast‑learner profile; lacks architect‑level public cloud breadth and container orchestration experience needed for a cloud architect role. **⚠️ Critical Gaps:** - Kubernetes / container orchestration (domain mismatch for cloud-native architectures) - Architect-level public cloud experience (designing multi-account/tenant cloud environments) **✅ Strengths:** - Proven system architect who builds production automation from concept to execution - Hands-on experience with on‑prem AI clusters and LLM deployments (privacy-focused) - Strong infrastructure automation skills (Terraform, Docker, CI/CD) and cross-domain domain expertise **❌ Missing Required:** DevSecOps demonstrated at scale (integration of security into CI/CD and infra pipelines), Public cloud architecture experience at an architect level (not just basic AWS knowledge)

[ANALYSIS_REPORT] **WEAK_MATCH** [Copilot: gpt-4.1] The candidate is a highly experienced solution architect with strong technical and domain expertise, matching most core requirements. However, there is no explicit evidence of the required professional certifications (Java/Oracle/Agile) or a postgraduate degree in Software Engineering, which are critical for this role. All other technical and architectural skills are present or strongly inferred. **⚠️ Critical Gaps:** - Required professional certifications (Java/Agile) or postgraduate degree in Software Engineering **✅ Strengths:** - Solution architecture and integration - Automation and DevOps (CI/CD, scripting) - Business-technology alignment and leadership **❌ Missing Required:** At least two of the listed professional certifications OR a postgraduate degree in Software Engineering

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] O candidato demonstra forte senioridade em arquitetura de sistemas, liderança e infraestrutura (Docker, CI/CD, Linux), alinhando-se com os deveres principais do cargo. A sua trajetória de carreira e capacidade de autoaprendizagem são impressionantes. No entanto, existe uma lacuna tecnológica crítica, com a sua especialização em Python a contrastar com a exigência da vaga por Node.js/Nestjs e pelo ecossistema Azure. **⚠️ Critical Gaps:** - Backend stack mismatch: Candidate has Python expertise vs. required Node.js/Nestjs **✅ Strengths:** - Systems Architecture & Design - Infrastructure Automation (Docker, CI/CD) - Proven Leadership & Project Ownership **❌ Missing Required:** Nodejs, Nestjs, Azure DevOps, Azure Pipelines, OpenShift, SonarQube, Jenkins

[ANALYSIS_REPORT] **WEAK_MATCH** [Copilot: claude-sonnet-4.5] Strong technical foundation with proven systems architecture experience and AI infrastructure expertise. However, lacks direct public sector experience and several critical enterprise-scale requirements. The candidate demonstrates 'fast learner' potential through self-taught AI implementations and complex system builds, but missing specific government sector knowledge and multi-cloud certifications that are explicitly required. **⚠️ Critical Gaps:** - Experiência direta com setor público/governamental - REQUISITO EXPLÍCITO - Vivência em projetos de grande porte em ambientes governamentais - Conhecimento de regulamentos e restrições do setor público brasileiro **✅ Strengths:** - Arquitetura de sistemas complexos do zero (JIT inventory com >95% accuracy, zero-touch operations) - Infraestrutura de IA local e otimização (Mac Studio M3, GPU clusters, LLMs self-hosted) - Background híbrido técnico-negócio (Supply Chain + Finanças + Engenharia) - ideal para traduzir necessidades governamentais em soluções **❌ Missing Required:** Experiência como pré-vendas técnico ou arquiteto de soluções em contexto empresarial, Projetos de grande porte/missão crítica documentados, Arquiteturas Multi-Cloud em ambiente de produção, Migração cloud-to-cloud demonstrada, Conhecimento profundo de ecossistema tecnológico do setor público

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] The candidate is an exceptionally strong technical architect with deep, modern experience in AI, automation, and systems integration, making him a near-perfect fit for the role's technical demands. The score is reduced due to a lack of direct pre-sales experience and significant logistical challenges posed by his location (Brazil) for an EMEA-focused role. **✅ Strengths:** - Deep, hands-on AI infrastructure experience (self-hosted LLMs) - Proven ability to architect and build automated systems (JIT inventory) - Strong background in data analytics and modern architecture (CI/CD, Docker) **❌ Missing Required:** Direct pre-sales experience

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] The candidate is a strong fit due to extensive experience in designing and building complex, automated data-driven systems from scratch, which strongly correlates with the required ETL/pipeline design skills. While lacking direct experience with the specific Azure data stack and data governance (LGPD), their proven track record as a fast learner, strong foundation in Python, SQL, and general cloud principles (AWS) suggests they can bridge these gaps quickly. **✅ Strengths:** - Proven ability to architect complex automated systems - Strong Python and SQL skills applied to data-heavy problems - Rapid learning and adaptation to new technologies (AI/Cloud) **❌ Missing Required:** Experiência em ferramentas Microsoft Azure (ADF, Synapse, Databricks, etc.), Conhecimento em governança de dados e LGPD

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] O candidato é um forte arquiteto de sistemas com experiência comprovada em Python, SQL e conceitos de arquitetura de dados, alinhando-se com os requisitos fundamentais. No entanto, faltam-lhe competências nas ferramentas específicas do Azure (Data Factory, Data Lake), que são centrais para a função. Sua capacidade de aprendizado rápido e experiência adjacente em nuvem (AWS) sugerem que ele pode preencher essas lacunas rapidamente, tornando-o uma boa combinação com potencial. **✅ Strengths:** - Arquitetura de Sistemas (do metal à produção) - Desenvolvimento em Python com aplicação em dados e automação - Histórico comprovado de aprendizado rápido e auto-didatismo em IA **❌ Missing Required:** Conhecimento de AZURE (possui apenas noções de AWS), Conhecimento Data Factory, Conhecimento Data Lake

[ANALYSIS_REPORT] **STRONG_MATCH** [Copilot: gpt-4.1] The candidate exceeds all hard skill requirements for the internship: strong cloud, database, and general technology knowledge, advanced Excel, and fluent English. Their experience in infrastructure, automation, and project management is far above the internship's expectations. No critical or required hard skill gaps are present; only Spanish (nice-to-have) is missing. **✅ Strengths:** - Infraestrutura e Nuvem - Excel avançado e análise - Comunicação bilíngue (Inglês/Português)

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Pro] The candidate is a highly capable systems architect and engineer with a proven track record of building complex, automated systems. However, this is a specialized Data Architect role, and the candidate shows significant gaps in core requirements like data lakehouse architecture, data streaming platforms (Kafka), and deep cloud experience, focusing more on on-premise infrastructure. **✅ Strengths:** - Proven ability to architect complex automated systems (JIT inventory, LLM clusters) - Strong Python, CI/CD, and infrastructure-level skills - Demonstrated fast learner with a strong career trajectory towards technical depth **❌ Missing Required:** Sólido conhecimento em arquiteturas de dados como data lakehouse, data warehouse, Conhecimento em implementação de streaming de dados, como Apache Kafka, Conhecimento aprofundado na nuvem da AWS (resume mentions only basics)

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] Good match on core architectural and DevOps skills, with a proven track record of designing and building complex, automated systems from scratch. The candidate's low stated experience in major cloud platforms (AWS/Azure/GCP) and lack of specific modeling language skills (UML/C4) are notable gaps, and the geographic location mismatch requires clarification. **⚠️ Critical Gaps:** - Requires hybrid (3x/week in-person) work in São Paulo, while candidate is 'Based in Brazil'. Feasibility needs to be confirmed. **✅ Strengths:** - Deep experience in automation and system design (JIT & trading bots) - Direct experience with core DevOps tools (Terraform, Docker, CI/CD) - Strong security foundation (SSO, RBAC, Local AI Privacy) **❌ Missing Required:** Experiência em plataformas como Azure, AWS ou GCP (resume lists 'noções básicas'), Uso de UML, C4 Model, e ferramentas similares ao ArchiMate

[ANALYSIS_REPORT] **POOR_FIT** [Copilot: gpt-5] Strong builder with Python/SQL and systems architecture, but the role requires deep SAP BDC and modern data platform leadership (Databricks/Snowflake/Kafka/Lakehouse) plus enterprise data governance experience absent here; fast-learner potential noted, yet the executive scope needs immediate platform depth. **⚠️ Critical Gaps:** - Deep SAP BDC and broader SAP data platform expertise - Hands-on Databricks/Snowflake/BigQuery leadership - Kafka/Event Streaming at enterprise scale - Lakehouse implementations and patterns - Enterprise data governance/lineage/MDM frameworks **✅ Strengths:** - Systems architecture and automation from concept to production - Python/SQL for data-driven solutions - Supply chain analytics and ROI-focused design **❌ Missing Required:** Solid SAP platform understanding (BDC, Datasphere, SAC, BW/4HANA, HANA Cloud), Deep understanding of Databricks/Snowflake/BigQuery and Lakehouse patterns, Kafka/Event streaming expertise, Strong governance, security, and compliance orientation (data lineage, MDM, regulations), Experience integrating SAP with external data platforms, Commercial/pricing understanding of SAP BDC

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a POOR_FIT due to a critical domain mismatch. While they have extensive experience in systems architecture, backend development, and the supply chain domain, the role is for a Visualization Architect specializing in Power BI. The candidate's resume shows no experience with the required core technologies like Power BI, DAX, or Snowflake. **⚠️ Critical Gaps:** - The role requires an expert in front-end data visualization (Power BI), while the candidate is a specialist in backend infrastructure and systems architecture. **✅ Strengths:** - Deep experience in the Supply Chain domain - Strong Python and automation skills - Proven ability to architect and build complex systems from scratch **❌ Missing Required:** 10+ years of experience in Business Intelligence Visualization, Expert-level proficiency in DAX and Power Query (M language), Strong experience with Snowflake, Experience with Azure Data Services, Experience with Power BI Service

[ANALYSIS_REPORT] **WEAK_MATCH** [Copilot: gpt-5-mini] Strong systems-architecture, automation and supply-chain/ERP domain experience indicate quick ramp-up potential, but the role requires deep, proven SAP S/4HANA architecture and module expertise which is not present on the resume. **⚠️ Critical Gaps:** - SAP S/4HANA architecture experience (role is architect-level and this is core) - Deep functional mastery of required S/4 modules (FI/CO, MM, SD, PP, PM, AA, TRM, Fiscal) - Greenfield S/4HANA implementation experience - Knowledge and application of SAP Activate / Clean Core / Fit-to-Standard (methodologies expected) **✅ Strengths:** - Hands-on systems architecture and infrastructure (metal-up, clusters, Docker/Terraform) - Deep supply-chain / ERP process knowledge (JIT, procurement, inventory automation) - Strong automation and integration experience (APIs, pipelines, production deployments) **❌ Missing Required:** Proven Arquiteto SAP S/4HANA on complex programs, Greenfield or deep ERP transformation delivery for S/4HANA, Domain experience in Utilities/Energy (regulated sector) specific to SAP IS-U or similar, Applied knowledge of SAP Best Practices, Activate and Clean Core approaches

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a highly skilled Systems Architect with a strong track record in automation and infrastructure, but possesses a critical domain gap. The role requires deep expertise in the ServiceNow platform and ITIL/ITSM processes, none of which are present in the candidate's resume. While technically proficient and a proven fast learner, the lack of platform-specific experience makes this a poor fit. **⚠️ Critical Gaps:** - ServiceNow Platform Expertise - IT Service Management (ITSM) Domain Knowledge **✅ Strengths:** - Strong Systems Architecture Experience (10+ years) - Proven Automation & End-to-End Systems Integration - Fast Learner with Diverse Technical Background (AI, Finance, Supply Chain) **❌ Missing Required:** 5+ years of ServiceNow-specific experience, ITIL Process definition, ServiceNow custom application design and development, Experience leading implementations in ITSM, ITOM, HRSD, etc.

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] Candidate is a STRONG_MATCH based on extensive experience in systems architecture, infrastructure design, and building complex automated systems from scratch. While direct, deep AWS experience is limited, their proven ability to self-teach complex technical domains (AI infrastructure, algorithmic trading) and their career trajectory towards infrastructure roles strongly suggest they can bridge this gap quickly. Their mindset aligns perfectly with a Solutions Architect role. **✅ Strengths:** - Proven systems architect with end-to-end project delivery - Demonstrated fast learner in complex technical domains - Strong connection between business logic (Supply Chain, Finance) and technical implementation **❌ Missing Required:** Deep experience with AWS services (resume indicates 'AWS Basics')

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a strong Systems Architect with proven experience in designing and building complex automated systems. However, there is a critical and disqualifying gap in Salesforce expertise, which is the core requirement of the role. Additionally, the required experience with Java and specific integration platforms like MuleSoft or Kafka is entirely absent. **⚠️ Critical Gaps:** - Salesforce platform expertise - Java for legacy systems **✅ Strengths:** - Solutions Architecture experience - Proven ability to automate complex systems from scratch - Strong self-teaching and fast-learning track record **❌ Missing Required:** Salesforce expertise (2+ years), Java-based solutions, MuleSoft, Kafka, Apigee, Hospitality industry experience

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] The candidate is a strong systems architect with proven experience building complex, data-intensive automated systems from scratch. While they lack direct experience with the specific AWS Big Data services (EMR, Glue) and technologies (Spark, Hadoop) required, their deep skills in Python, IaC (Terraform), and architectural design, combined with a demonstrated fast-learning ability, make them a high-potential fit. **✅ Strengths:** - Proven Systems Architecture from concept to production - Advanced Python for data processing and automation - Strong foundation in modern infrastructure (IaC with Terraform, Docker, CI/CD) **❌ Missing Required:** Direct experience with specific AWS Big Data services (e.g., EMR, Glue, Kinesis), Experience with at least two of the following: Hadoop, Spark, EMR, Streaming/Messaging (Kafka, etc.), NoSQL, Caching, Search

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] The candidate is a strong conceptual match, demonstrating deep, self-taught expertise in AI infrastructure and systems architecture. His trajectory towards AI is ideal. However, the profile shows significant gaps in required enterprise-level skills like deep cloud architecture (AWS/GCP/Azure) and formal API governance, which are central to the role. **✅ Strengths:** - Hands-on AI infrastructure experience (self-hosted LLMs) - Proven systems architecture and end-to-end project execution - Strong background in financial markets and algorithmic logic **❌ Missing Required:** Experiência com arquitetura em nuvem (AWS, GCP ou Azure), Experiência na definição e implantação de governança de APIs, Conhecimento em API Gateways, rate limits, observabilidade e monitoração, Compliance regulatório (LGPD, PCI DSS), Familiaridade com DLT

[ANALYSIS_REPORT] **WEAK_MATCH** [Copilot: gpt-5] Strong architecture, Python/SQL and infra-as-code; missing Databricks/Spark and multi-cloud proficiency for a Data Architect lead role, but fast-learner potential is evident. **⚠️ Critical Gaps:** - Databricks - Apache Spark - Lakehouse/Delta Lake **✅ Strengths:** - Systems architecture & automation - Python/SQL for data processing - Infra-as-code & containerization (Terraform/Docker) **❌ Missing Required:** Databricks, Apache Spark, Delta Lake/Lakehouse, Azure, GCP

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] The candidate is a strong systems architect with proven experience in building complex automation from the ground up, particularly with Python, APIs, and CI/CD. However, there is a critical gap regarding direct experience with enterprise RPA platforms (UiPath, Automation Anywhere), which is a core requirement. His fast-learner profile and career trajectory towards automation make him a high-potential candidate, but he would require significant ramp-up on the specific tools. **⚠️ Critical Gaps:** - Domínio em plataformas RPA (UiPath, Automation Anywhere, Blue Prism ou similares) **✅ Strengths:** - Arquitetura de Sistemas e Integração (API, ERP) - Automação de Processos de ponta-a-ponta com Python - Rápida capacidade de aprendizado e adaptação a novas tecnologias **❌ Missing Required:** Modelagem de processos (BPMN), Vivência com orquestração e escalabilidade de robôs RPA

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] The candidate demonstrates strong, hands-on expertise in several core required areas, including Python, Containerization (Docker), and Infrastructure as Code (Terraform). Their background building complex, automated systems from the ground up proves a high degree of technical aptitude and problem-solving skills. The primary gaps are the lack of direct experience with Observability platforms and not meeting the 10-15 years specifically in a customer-facing role, though their founder and freelance experience is relevant. **✅ Strengths:** - Excellent hands-on skills in Python, Docker, Terraform, and CI/CD - Proven "fast learner" with a track record of self-teaching complex domains (AI Infra, Algo-Trading) - Career trajectory shows intentional progression towards complex systems architecture **❌ Missing Required:** 10-15 years of experience in a customer or partner facing technical role, Hands-on experience in Observability (Datadog, Splunk, New Relic, etc.)

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] The candidate is a strong technical and cultural fit, with a proven track record of architecting and building complex systems from the ground up, which aligns with the core responsibilities of a Solutions Architect. While lacking direct experience with the GitLab platform and Spanish, their deep expertise in underlying DevSecOps technologies (CI/CD, Docker, Git) and rapid learning ability make them a high-potential candidate. **✅ Strengths:** - Deep systems architecture experience from 'metal-up' - Hands-on with core DevOps tools (CI/CD, Git, Docker, Python) - Proven fast learner with a clear career trajectory towards AI/Infrastructure roles

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] The candidate is an exceptionally strong match due to demonstrated, hands-on experience in self-hosting AI/LLM clusters on GPUs, which directly aligns with NVIDIA's core technology stack. Their career trajectory from business domains (Finance, Supply Chain) to deep technical infrastructure shows a perfect blend for a Solutions Architect. The proven ability to self-teach complex topics and build production-grade systems from scratch indicates a high aptitude for the role's demands. **✅ Strengths:** - Hands-on GPU/AI infrastructure experience (self-hosted LLMs) - Proven ability to architect and build automated, production-grade systems - Ideal career trajectory for a business-to-technology 'Bridge' role **❌ Missing Required:** Creative generation of synthetic data

[ANALYSIS_REPORT] **WEAK_MATCH** [Copilot: claude-sonnet-4.5] Candidate demonstrates strong systems thinking, automation expertise, and foundational cloud knowledge (Docker, Terraform, AWS basics). However, lacks specific Microsoft Azure experience and hands-on expertise with core Azure services (AKS, vNets, RBAC, Azure Monitor). The role requires deep Azure proficiency, not just cloud fundamentals. Strong architectural mindset and fast-learner profile with proven ability to build complex systems (JIT inventory, AI infrastructure) suggests capability to bridge gaps with focused training. Age (33) and autodidact background support adaptability, but the Azure specialization gap is significant for a senior architect role. **⚠️ Critical Gaps:** - Zero demonstrated Microsoft Azure experience (job specifically requires 'sólida experiência em arquitetura de nuvem, preferencialmente em Microsoft Azure') - No Azure certification pathway mentioned - Limited Kubernetes/container orchestration at scale **✅ Strengths:** - Proven systems architect with end-to-end delivery (JIT inventory system, AI infrastructure) - Strong automation and IaC foundation (Terraform, Python, scripting) - Business-technical bridge with supply chain and financial domain expertise (valuable for FinOps and cost-efficient solutions) **❌ Missing Required:** Microsoft Azure hands-on experience, Azure vNets and networking, Azure RBAC and Policies, AKS (Azure Kubernetes Service), Azure monitoring stack (Monitor, Log Analytics, App Insights), Azure DevOps or CI/CD on Azure, Cloud migration strategies (Azure-specific), Azure modernization experience

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] Excelente candidato para o pipeline de Arquitetura de Soluções. Demonstra forte experiência prática na construção de sistemas escaláveis e resilientes (e-commerce JIT, clusters de IA) e mentalidade cloud-native (Docker, Terraform). As lacunas estão em tecnologias específicas como mensageria e cache, mas seu histórico de autoaprendizagem sugere que ele pode adquiri-las rapidamente. **✅ Strengths:** - Arquitetura de sistemas distribuídos ponta a ponta - Mentalidade cloud-native com experiência em Docker/Terraform - Capacidade comprovada de autoaprendizagem e aplicação de tecnologias emergentes (IA) **❌ Missing Required:** mensageria, logs estruturados, cache

[ANALYSIS_REPORT] **WEAK_MATCH** [Copilot: gpt-5-mini] Strong systems-architecture, automation and Linux/Docker experience with demonstrated fast-learning and on-prem AI cluster ops, but lacks enterprise Oracle DBA expertise, OCI and managed AWS DB/Kubernetes experience required for critical DB migration/modernization work. **⚠️ Critical Gaps:** - Oracle Database + RMAN + Data Guard + GoldenGate (enterprise Oracle DBA domain) - Exadata (hardware/platform-specific Oracle experience) - OCI (cloud vendor required by role) - AWS RDS / EKS (managed DB and Kubernetes experience for migrations) - Kubernetes (production orchestration for containerized DB/workloads) **✅ Strengths:** - Systems architecture and end-to-end automation - Hands-on experience with on-prem AI/GPU clusters and LLM deployment - Strong Python + scripting + CI/CD automation background **❌ Missing Required:** Experiência sólida como DBA Oracle Sênior, Oracle Database, RMAN, Data Guard, GoldenGate, Exadata, OCI, AWS RDS and EKS (production), Kubernetes, Proven on-prem → cloud DB migration experience

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] O candidato é um forte arquiteto de sistemas com profunda experiência em automação (Python, IaC) e infraestrutura, e sua trajetória de carreira e background financeiro são muito relevantes. No entanto, existem lacunas significativas na experiência direta com o desenho de arquiteturas em nuvens públicas (AWS/Azure em nível avançado) e tecnologias BigData, que são requisitos imprescindíveis para a vaga. **✅ Strengths:** - Forte experiência em arquitetura de sistemas e automação (Python, Terraform) - Capacidade comprovada de autoaprendizagem e adaptação a novas tecnologias - Trajetória de carreira com progressão clara para papéis de alta complexidade técnica **❌ Missing Required:** Experiência comprovada em desenhar Arquitetura de Soluções utilizando cloud pública AWS / Azure, Experiência comprovada em desenhar Arquitetura de Soluções com tecnologia BigData, Uso de ferramentas Jira e Confluence, Conhecimento de uso de ferramentas de EA (Arquitetura Empresarial)

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: gpt-5-mini] Strong systems architect with 10+ years building production systems, automation, AI/ML infra and CI/CD; demonstrates fast-learning and hands-on delivery. Major mismatches are enterprise cloud and the company's primary dev stacks but these are learnable given the candidate's demonstrated breadth and on-prem cluster experience. Optimistic fit for an architecture role after a short ramp on cloud and backend stack specifics. **⚠️ Critical Gaps:** - .NET / Java / Node.js (primary backend stacks listed by employer) - Advanced cloud architecture and managed services (AWS/Azure/GCP) **✅ Strengths:** - System architecture and end-to-end production delivery - AI/ML infrastructure and local LLM deployment experience - Automation and operational resilience (Docker, Terraform, CI/CD, scripting) **❌ Missing Required:** .NET or Java or Node.js experience, Clear hands-on experience with microservices & event-driven patterns at scale, Demonstrable advanced cloud (AWS/Azure/GCP) usage and managed services, Experience with enterprise RDBMS commonly cited (SQL Server/Oracle) and NoSQL like MongoDB, Formal use of UML/C4 or equivalent architectural diagramming in enterprise projects

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: gpt-5-mini] Strong Python, SQL (MySQL/Postgres), engineering and infra background (Docker, Linux, Git, CI/CD) and demonstrated data pipeline + ML ops experience indicate high fast‑learner potential; however the role expects hands‑on Big Data stack (PySpark/Spark, Hive, NIFI, enterprise DBs/Erwin) which are not shown and are important for immediate impact. **⚠️ Critical Gaps:** - PySpark / Apache Spark (core + SparkML) - Hive - Apache Nifi - Enterprise RDBMS experience: DB2 and Oracle - Data modeling with Erwin **✅ Strengths:** - Strong Python + SQL development and data manipulation experience - Robust infrastructure/ops skills (Docker, local GPU clusters, Terraform, Linux) - Proven track record building production automation and data pipelines (fast learner) **❌ Missing Required:** PySpark, Spark / SparkML, Hive, NIFI, DB2, Oracle, Erwin, HUE

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a proven Systems Architect with strong skills in cloud, automation, and AI infrastructure. However, there is a critical domain gap, as they lack the required, specialized experience in telecommunications, mobile networks, and specific protocols (MVNO, 5G, MAP, DIAMETER) that are central to this role. **⚠️ Critical Gaps:** - Telecommunications & Mobile Network Engineering (MVNO, 5G, MAP, CAMEL, etc.) **✅ Strengths:** - Proven Solutions Architecture experience - Strong cloud and virtualization skills (Docker, Terraform) - Demonstrated fast learner with AI/ML infrastructure expertise **❌ Missing Required:** Excellent understanding of Mobile Networks and its architectures, Experience with MVNO architecture(s) and landscape, Experience in network protocols like MAP, CAMEL, SIGTRAN, DIAMETER, SIP, Knowledge and experience of OCS and Gy/Sy interfaces, Experience with VoLTE and VoWiFi, Experience with LTE, 5G, IMS, Experience with 5G Core Mobile Networks

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: claude-sonnet-4.5] Strong architectural thinking and systems integration background aligns well with BCG Platinion's technical consulting model. Candidate demonstrates proven ability to design complex systems (JIT automation, AI infrastructure) and bridge business-technical gaps. However, lacks formal consulting experience and some enterprise-specific technologies. The 'builder' profile fits the hands-on MVP/POC requirements, but 6-10 years experience requirement is borderline met with relevant technical work. **✅ Strengths:** - Strong systems architecture & integration mindset - proven ability to design complex, automated systems from scratch (JIT inventory, AI infrastructure) - Hybrid business-technical profile - Supply Chain + Finance background enables effective translation between business requirements and technical solutions (exactly what BCG Platinion needs) - Hands-on technical depth with modern stack - Python, Docker, Terraform, CI/CD, SQL databases, and emerging AI/ML technologies demonstrate ability to build POCs and MVPs **❌ Missing Required:** Formal consulting experience (technology/digital delivery consulting), Enterprise IT target architecture assessment experience, Service-oriented architectures (SOA) experience, Hadoop/big data platform exposure

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: claude-sonnet-4.5] Strong foundational match with significant transferable skills. Candidate demonstrates technical depth (Python, Docker, Terraform, AWS basics, SQL), business acumen (Supply Chain, Finance background), and proven ability to bridge technical-business gaps. The 10+ years combining technical execution with business strategy aligns well with the SME role. However, lacks specific Microsoft/Azure ecosystem experience and required certifications (AZ-104, AZ-900). The 'Fast Learner' profile is evident through self-hosted AI infrastructure and automated e-commerce systems. Age (33) and system-building track record suggest strong learning velocity, making certification gaps surmountable within 3-6 months. **✅ Strengths:** - Proven Technical-Business Bridge: 10+ years translating business objectives to technical infrastructure (Supply Chain → Finance → Systems Engineering), directly aligns with SME role requirements - Hands-on Cloud & Infrastructure: Docker, Terraform, AWS basics, CI/CD pipelines, and self-hosted AI clusters demonstrate practical cloud concepts and migration readiness - System Design & Automation Expertise: Built production-grade automated inventory system (>95% accuracy, zero daily maintenance) proves ability to understand complex solutions and communicate value propositions **❌ Missing Required:** AZ-104 Certification (Required), AZ-900 Certification (Required), Microsoft Partner Program Experience, Pre-sales or Technical Sales Support (2-4 years)

[ANALYSIS_REPORT] **WEAK_MATCH** [Copilot: gpt-5-mini] Strong systems architecture, Python ETL skills and supply-chain/ERP domain knowledge signal good learning potential, but the candidate lacks direct SAP S/4HANA migration and SAP-tooling experience that are core to the role. **⚠️ Critical Gaps:** - SAP S/4HANA migration experience - ABAP for data transformation - Hands-on with SAP Migration Cockpit - SLT/SDI or equivalent SAP replication tools - Ability to interpret SUM/DMO and trial conversion logs **✅ Strengths:** - Systems architecture and infrastructure (local IA clusters, production deployments) - Python-driven data pipelines, automation and scripting - Supply chain / ERP domain knowledge and practical JIT system design **❌ Missing Required:** Proven migration to SAP S/4HANA (brownfield/selective), Hands-on SAP Migration Cockpit, ABAP experience for data routines, SLT/SDI, BAPIs, IDocs experience, SUM/DMO and conversion pre-check troubleshooting, Deep understanding of ACDOCA / Universal Journal and BP model

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] Excelente alinhamento com os requisitos de infraestrutura de IA e orquestração de contêineres. O candidato demonstra experiência profunda na construção de sistemas de IA do zero ("self-hosted LLMs"), que excede a exigência de simplesmente usar ferramentas como Docker Model Runner. Embora faltem palavras-chave para ferramentas específicas como LocalStack e Test Containers, suas habilidades fundamentais em Docker, Linux e CI/CD, combinadas com uma trajetória de carreira relevante, o tornam um candidato excepcional. **✅ Strengths:** - Deep experience with AI infrastructure (self-hosted LLMs) - Advanced containerization and automation skills (Docker, Python, CI/CD) - Proven ability to architect and build production-grade systems from scratch **❌ Missing Required:** LocalStack, Test Containers, Dev Containers, Docker Hub analytics