[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] The candidate is an exceptionally strong fit. They demonstrate deep, hands-on experience in architecting and deploying complex, automated systems from the ground up (JIT inventory, self-hosted AI), aligning directly with the core responsibilities of a technical architect. Their career trajectory shows a deliberate and successful pivot into advanced AI infrastructure, and their proven 'fast learner' profile suggests they can rapidly adapt to BCG's client needs and technologies. **✅ Strengths:** - Proven 'metal-up' systems architecture (JIT System, AI Clusters) - Deep expertise in Python, automation, and data-driven systems - Clear progression from business domains to complex technical/AI roles

[ANALYSIS_REPORT] **WEAK_MATCH** [Copilot: gpt-4.1] The candidate demonstrates strong architecture, automation, and cloud fundamentals, with proven leadership and hands-on delivery. However, there is no direct evidence of Azure Cloud expertise, FinOps/cost optimization at scale, or large enterprise cloud migrations—these are critical for the role. The candidate's fast learning, systems thinking, and experience with AWS basics, Docker, and Terraform are strong positives, but the lack of Azure and FinOps is a significant gap. **⚠️ Critical Gaps:** - Azure Cloud (deep, hands-on expertise) - FinOps (proven cost optimization in cloud environments) **✅ Strengths:** - Systems Architecture & Automation - Technical Leadership & Project Delivery - Fast Learning and Adaptability **❌ Missing Required:** Azure Cloud (5+ years, hands-on), FinOps/Cloud Cost Optimization

[ANALYSIS_REPORT] **WEAK_MATCH** [Copilot: gpt-5] Strong systems architect and automation background, but lacks core Java 17 and Azure APIM experience plus specific architecture frameworks required; fast learner potential mitigates slightly. **⚠️ Critical Gaps:** - Java 17/Microservices - Azure APIM **✅ Strengths:** - Systems architecture and automation experience - CI/CD and DevOps tooling (Docker/Terraform) - Security/identity (SSO, RBAC) with governance mindset **❌ Missing Required:** Java 17, Java Microservices, Azure APIM, TOGAF experience, Hexagonal Architecture, Event-driven Architecture, MVC, Clean Code, SOLID, TDD/BDD, Experience in Agile DevOps environment

[ANALYSIS_REPORT] **WEAK_MATCH** [Copilot: gpt-5-mini] Strong systems architecture, Docker/Terraform and Python/AI infra experience and demonstrated ability to build production systems quickly, but missing several core platform and language requirements (advanced Java, Kubernetes, specific CI/CD tooling and front-end/testing stacks) that this role lists as mandatory. **⚠️ Critical Gaps:** - Java (Spring Boot / Hibernate) - role requires advanced Java development - Kubernetes - required for container orchestration and security **✅ Strengths:** - Systems architecture and end-to-end production deployments - AI/ML infrastructure and local LLM hosting (privacy-focused) - Automation with Python, Docker and Terraform **❌ Missing Required:** Advanced Java (Spring Boot, Hibernate), Kubernetes, Specific CI/CD platforms (Azure DevOps/Jenkins/GitLab CI), Front-end frameworks and TypeScript, Automated UI testing frameworks (Selenium/Robot/Cypress)

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: claude-sonnet-4.5] Strong architectural and technical foundation with proven system design experience. Candidate demonstrates advanced problem-solving (automated JIT inventory, AI infrastructure) and relevant domain expertise (supply chain, product strategy). The 10+ years bridging business-tech aligns well with Accenture Song's SME + strategic collaboration role. Main gap: limited explicit client-facing consulting experience and Portuguese market/culture familiarity assumed but not explicitly stated for São Paulo role. **✅ Strengths:** - Proven Solution Architect: Built production-grade automated systems from scratch (JIT inventory >95% accuracy, zero manual intervention) - Business-Tech Bridge: 10+ years translating business objectives into technical infrastructure across finance, supply chain, and e-commerce domains - Advanced Technical Depth: Python, Docker, Terraform, AI infrastructure, Clean Architecture, CI/CD pipelines—exceeds typical SA requirements **❌ Missing Required:** Advanced-level Requirements Analysis (formal methodology), Digital product lifecycle management (explicit experience), User enablement program development

[ANALYSIS_REPORT] **DISQUALIFIED** [Copilot: claude-sonnet-4.5] This is a critical domain mismatch. The role requires 5-7+ years of specialized UiPath RPA development experience and mandatory UiPath certifications. The candidate has strong systems architecture, Python automation, and infrastructure skills but zero demonstrated RPA platform experience (UiPath, Automation Anywhere, Blue Prism). While the candidate shows 'Fast Learner' potential and relevant automation thinking, the 5-7 year UiPath requirement cannot be met through quick learning—this represents years of platform-specific expertise including REFramework, Orchestrator, AI Center, and enterprise RPA governance. The role is fundamentally about UiPath ecosystem mastery, not general automation architecture. **⚠️ Critical Gaps:** - Zero UiPath platform experience (requires 5-7+ years hands-on) - No RPA platform experience whatsoever (UiPath/AA/Blue Prism) - Missing mandatory UiPath certifications (UiARD/Solution Architect) - No demonstrated RPA solution architecture experience - No enterprise RPA governance or CoE experience **✅ Strengths:** - Strong general automation and systems integration background (10+ years IT experience requirement met) - Proven track record building production-grade automated systems (JIT inventory, trading bots) - Python expertise with data processing (Pandas) - transferable to RPA scripting and data manipulation - API integration experience (relevant for UiPath enterprise system connections) - Systems architecture mindset with focus on scalability, resilience, and ROI **❌ Missing Required:** 5-7+ years UiPath hands-on experience, UiPath Advanced Developer Certification, UiPath Solution Architect Certification, REFramework expertise, UiPath Orchestrator administration, RPA lifecycle experience (Discovery-Design-Development-Testing-Deployment-Maintenance), VB.NET scripting, RPA-specific security and compliance patterns

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: gpt-4.1] O candidato demonstra forte experiência em arquitetura de sistemas, automação, IA local, pipelines de dados e integração de APIs, além de habilidades sólidas em Python, SQL, Docker, Terraform e fundamentos de AWS. No entanto, faltam evidências diretas de experiência prática e profunda com serviços AWS específicos para Data & GenAI (S3, Glue, Redshift, Athena, Bedrock, SageMaker, Lambda), atuação prévia em pré-vendas técnicas, certificações AWS e participação ativa em comunidades AWS. O perfil é de rápido aprendizado e alta senioridade técnica, mas há lacunas críticas para o papel de referência em AWS Data & GenAI. **⚠️ Critical Gaps:** - Experiência prática e profunda com serviços AWS Data & GenAI (S3, Glue, Redshift, Athena, Bedrock, SageMaker, Lambda) - Certificações AWS - Atuação comprovada em pré-vendas técnicas no ecossistema AWS **✅ Strengths:** - Arquitetura de sistemas complexos e automação ponta a ponta - Experiência prática com IA, ML e integração de dados - Capacidade de conectar objetivos de negócio à tecnologia **❌ Missing Required:** Experiência sólida em pré-vendas técnicas no ecossistema AWS, Certificações AWS, Experiência comprovada com serviços AWS Data & GenAI

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] Candidate is an almost perfect fit, demonstrating exceptional systems architecture experience by building complex, automated platforms from the ground up. His career trajectory uniquely bridges business domains like supply chain with deep technical implementation, including self-hosted AI infrastructure. The only minor gap is extensive experience in a specific managed cloud ecosystem, which is heavily mitigated by his proven ability to rapidly master and deploy complex technologies. **✅ Strengths:** - Proven Systems Architect with end-to-end project execution - Unique ability to translate business requirements (Supply Chain, Finance) into technical ROI - Demonstrated fast learner with hands-on experience in modern, complex infrastructure (AI Clusters, Docker)

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] The candidate is a strong Systems Architect with a proven ability to connect business needs to technical infrastructure, particularly in security and automation. However, there is a critical gap in direct experience with the required Big Data stack (Spark, Kafka, Airflow, Snowflake). Their rapid learning ability and strong adjacent skills (Python, SQL, Terraform) suggest they could bridge this gap, making them a good but not perfect match. **⚠️ Critical Gaps:** - Experience with modern distributed data platforms (Spark, Kafka, Snowflake, etc.) is almost entirely absent; the candidate's experience is in self-hosted/on-prem systems, not a cloud-native Big Data stack. **✅ Strengths:** - Strong systems architecture and automation skills (Terraform, Python, CI/CD). - Proven ability to translate business requirements (Finance, Supply Chain) into technical ROI-focused solutions. - Deep experience in security and privacy-focused implementations (SSO, RBAC, On-prem AI). **❌ Missing Required:** Spark, Kafka, Airflow, Databricks, Snowflake, BigQuery

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] The candidate is a strong fit, embodying the 'builder' profile AWS seeks. Their proven experience in architecting complex, automated systems from scratch and a career trajectory moving towards AI/Systems architecture is ideal. The only minor gap is deep, demonstrated AWS-specific experience, which is heavily mitigated by a proven fast-learning track record and deep infrastructure knowledge. **✅ Strengths:** - Hands-on 'builder' profile architecting systems from the ground up (JIT, AI clusters). - Connects business requirements (Finance, Supply Chain) to technical ROI-focused solutions. - Proven fast learner with a strong ability to master new, complex technical domains independently. **❌ Missing Required:** Deep, demonstrated experience with a wide range of AWS services

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] Candidate is an exceptionally strong fit. He demonstrates deep, hands-on experience in systems architecture, Python, and SQL, directly aligning with core requirements. His background in building complex, automated systems (JIT inventory, AI clusters) from the ground up proves his ability to act as a trusted technical advisor. The career trajectory shows a clear and intentional progression towards this exact type of role, and his proven ability to self-teach complex technologies mitigates the lack of direct MongoDB experience. **✅ Strengths:** - Complex Systems Architecture & Integration - AI Infrastructure & Self-Hosted LLM Experience - Proven Fast Learner with Strong Business Acumen **❌ Missing Required:** Node.js

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a proven Systems Architect with strong experience in automation, infrastructure, and connecting business logic to technical systems. However, there is a critical and total gap regarding the core requirement: the SAP ecosystem. The role requires 10+ years of deep, specific experience in SAP technologies (S/4HANA, BTP, etc.), which the candidate does not possess. **⚠️ Critical Gaps:** - The role is exclusively focused on the SAP ecosystem, while the candidate's entire experience is with custom-built, open-source, and self-hosted systems (Python, Docker, local AI clusters). This is a fundamental domain mismatch. **✅ Strengths:** - Systems Architecture (non-SAP) - Automation & Process Optimization - Rapid learning and implementation of new technologies **❌ Missing Required:** 10+ years of experience with SAP solutions, S/4HANA, SAP Business Technology Platform, SAP Cloud projects, Cross-functional SAP modules (FI, CO, SD, MM), SAP tools for fit-gap analysis

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] Candidate is a very strong technical solutions architect with deep, modern skills in AI infrastructure, automation, and systems design. While he perfectly matches the 'Solution Architect' part of the title and the nice-to-have AI skills, he lacks any demonstrated experience in the core pre-sales and bid management responsibilities that dominate the job description. He is a high-potential technical fit who would need to be trained on the sales-cycle aspects of the role. **✅ Strengths:** - Expertise in AI/LLM Infrastructure - Proven End-to-End Systems Architecture - Strong Automation Skills (Python, CI/CD) **❌ Missing Required:** Bid Management / Proposal Lifecycle Experience, Proficient Cloud Platform Experience (Azure/Google/Oracle), Specific Data Platforms (Snowflake, Databricks)

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] The candidate is a strong systems architect with proven experience designing automated, production-grade systems from the ground up. He has direct experience with key required technologies like Terraform (IaC) and Docker. However, there is a critical gap in demonstrated experience with the specific AWS serverless stack (Lambda, SQS, API Gateway) which is a core requirement for the role. **⚠️ Critical Gaps:** - Deep expertise in AWS serverless services (Lambda, SQS, SNS, API Gateway) **✅ Strengths:** - Holistic system architecture from concept to production - Strong Infrastructure-as-Code (Terraform) and containerization (Docker) skills - Proven fast learner with a career trajectory towards complex technical roles **❌ Missing Required:** 5+ years as an Architect in enterprise environments, Strong expertise in serverless development using API Gateway, Lambda, S3, SNS, SQS, and CloudFront

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a strong systems architect and proven fast learner with a solid background in Python, SQL, and general system design. However, there is a critical gap, as they lack any demonstrated experience with the entire core data stack required for this role (Snowflake, DBT, Azure), making them a poor fit for this specific Senior Data Architect position. **⚠️ Critical Gaps:** - Lacks experience in the entire required data stack (Snowflake, DBT, Azure). Experience is in operational systems and local AI, not cloud data warehousing. **✅ Strengths:** - Proven fast learner with strong self-teaching track record in complex domains (AI, Algo-trading) - End-to-end systems architecture and automation experience - Strong transferable skills in Python, SQL, and general infrastructure **❌ Missing Required:** Snowflake, DBT, Azure Cloud Services, ELT

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a highly skilled Systems Architect with proven expertise in automation and building complex business logic from the ground up. However, there is a critical and complete gap in the required domain of Payroll and HR. The role is fundamentally about payroll compliance and process design, for which the candidate has no demonstrated experience, making it a poor fit despite strong adjacent technical skills. **⚠️ Critical Gaps:** - Lack of any experience in the Payroll or HR domain, which is the core requirement of the role. **✅ Strengths:** - Strong systems architecture and automation skills - Proven ability to translate complex business logic into technical systems - Fast learner with a track record of mastering new technical domains **❌ Missing Required:** Thorough understanding of Payroll and HR legislation, Strong understanding of Payroll administration and management processes, Experience with payroll systems

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Pro] The candidate possesses exceptional, hands-on experience in core AI infrastructure, including self-hosting LLMs, and modern systems architecture (APIs, Docker, Terraform). However, there is a critical gap in the client-facing and product design aspects of the role, with no demonstrated experience in UX/UI, prototyping tools, or formal pre-sales processes. While technically proficient, this makes the candidate a weak fit for a role that bridges business, design, and technology. **⚠️ Critical Gaps:** - UX/UI design and prototyping (Figma/Sketch) - Formal technical pre-sales and strategic consulting experience **✅ Strengths:** - Deep, hands-on experience with LLM infrastructure (self-hosted) - Proven ability in full-stack systems architecture and automation (JIT system) - Strong foundation in cloud-native technologies (Docker, Terraform, APIs) **❌ Missing Required:** RAG, LangChain, CrewAI frameworks, Experiência sólida em pré-vendas técnicas, Familiaridade com UX/UI e prototipagem (Figma/Sketch)

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a skilled Systems Architect but has zero experience with the Salesforce platform, which is the core requirement of the role. While they possess transferable skills in architecture, API integration, and automation, the complete absence of Sales Cloud, Service Cloud, Apex, or LWC expertise constitutes a critical domain gap. Their career trajectory is also moving towards AI Infrastructure, away from enterprise business applications like Salesforce. **⚠️ Critical Gaps:** - The role requires deep expertise in the Salesforce ecosystem (Sales/Service Cloud, Apex), while the candidate's experience is in custom Python-based systems, AI infrastructure, and supply chain automation. **✅ Strengths:** - Proven fast learner with a track record of self-teaching complex technical domains (AI, Algorithmic Trading). - Strong experience in systems architecture and designing automated, production-grade systems from scratch. - General experience with CI/CD pipelines, Git, and SQL databases, which are conceptually adjacent to some requirements. **❌ Missing Required:** 7+ years of hands-on Salesforce experience, Deep expertise in Sales Cloud (lead-to-cash, pipeline management, forecasting), Strong understanding of Service Cloud architecture (case routing, omni-channel), Proficiency in Salesforce configuration and development (Apex, Lightning Web Components)

[ANALYSIS_REPORT] **DISQUALIFIED** [Copilot: claude-sonnet-4.5] This is a highly specialized SAP S/4HANA Data Migration Architect role requiring deep SAP ecosystem expertise. The candidate has strong general systems architecture, data engineering, and automation skills, but lacks the specific SAP domain knowledge that is non-negotiable for this position. This is a domain-specific expert role, not a general architect position. **⚠️ Critical Gaps:** - Zero SAP ecosystem experience - this is a BLOCKING gap for an SAP-specific architect role - No enterprise ERP transformation experience in SAP landscape - Missing SAP-specific certifications that are expected for this seniority level - No demonstrated experience with SAP data structures or migration methodologies **✅ Strengths:** - Strong systems architecture and integration background with proven ability to design complex automated systems - Supply chain and procurement domain expertise aligns with MM/SD/EWM modules conceptually - Demonstrated 'fast learner' profile with self-taught AI/Cloud infrastructure and successful business automation **❌ Missing Required:** SAP data migration experience, SAP S/4HANA transformation program leadership, Deep S/4HANA data structure knowledge, SAP migration tools mastery, SAP module expertise across FI/CO/MM/SD/PP

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a highly skilled technologist and a proven fast learner with impressive experience in building complex automated systems. However, there are critical gaps as the role requires deep Health sector domain knowledge and a pre-sales background, neither of which are present in the candidate's history. The lack of the required Spanish language skill is also a major deficiency. **⚠️ Critical Gaps:** - Health sector domain knowledge - Customer-facing pre-sales experience **✅ Strengths:** - Proven ability to self-teach and master complex new domains (AI, Quant Trading) - Deep experience in systems architecture and building automated, production-grade systems - Strong hands-on experience with modern cloud and infrastructure technologies (Docker, Python, SQL) **❌ Missing Required:** Experiência prévia em atividades de pré-venda... voltadas ao setor de Saúde, Conhecimento de processos hospitalares, operadoras ou laboratórios, Espanhol Avançado

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a skilled systems architect with a strong, relevant background in systems integration and a proven ability to self-teach complex technologies. However, there is a critical and disqualifying gap in the core required technology: the entire Microsoft Identity ecosystem. Despite foundational knowledge of identity concepts like SSO/SAML, the complete lack of experience in Microsoft Entra ID, migrations, and PKI/ADCS makes this a poor fit. **⚠️ Critical Gaps:** - The role requires deep, end-to-end expertise in the Microsoft Entra ID stack, which is entirely absent from the candidate's resume. **✅ Strengths:** - Proven fast learner with a track record of mastering new technical domains. - Strong foundational knowledge of identity principles (SSO/OIDC/SAML, RBAC). - Extensive experience in systems architecture and automation. **❌ Missing Required:** Deep knowledge and experience in Microsoft Entra ID (End to End), Experience in managing cross-tenant migrations and synchronisation, Experience in Microsoft Entra ID PKI/ADCS solutioning

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Pro] The candidate is a strong systems architect with proven leadership and a remarkable ability to self-teach complex technologies. However, there is a critical gap in experience with the required enterprise data stack (Azure, Databricks, ADF), which is central to this Lead role. **⚠️ Critical Gaps:** - Deep experience with the Azure data ecosystem (Databricks, ADF) is required and entirely missing. **✅ Strengths:** - Proven Systems Architecture & Automation (JIT system) - Rapid learning & implementation of new tech (self-hosted LLMs) - Strong transferable domain knowledge (Supply Chain) **❌ Missing Required:** Azure, Databricks, Azure Data Factory (ADF), SAP

[ANALYSIS_REPORT] **DISQUALIFIED** [Copilot: gpt-5] Strong systems/automation background but lacks core mainframe stack and legacy code-analysis experience required for the role. **⚠️ Critical Gaps:** - Mainframe technologies (NATURAL/COBOL/CICS/IMS/JCL/DB2) - Hands-on assessments in mainframe environments - Legacy code-analysis tooling for mainframe **✅ Strengths:** - Systems architecture and automation (Python, Docker/Terraform) - CI/CD, Linux, DevOps foundations - ROI/TCO mindset and operational resilience focus **❌ Missing Required:** NATURAL, COBOL, CICS, IMS, JCL, DB2, Mainframe Batch/Online, Legacy system architectures, Legacy code analysis tools, Familiarity with modernization strategies (Rehosting/Replatforming/Refactoring/Rearchitecting)

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Pro] The candidate is a strong systems architect and infrastructure engineer with extensive experience in Python, Docker, and CI/CD, aligning with many backend requirements. The calculated score is high due to strong alignment on these foundational principles. However, there is a complete and critical gap in the required Node.js and React technology stack, making the candidate a high-risk choice for leading a team focused on those technologies. **⚠️ Critical Gaps:** - JavaScript-based technologies (Node.js, React) **✅ Strengths:** - Strong systems architecture and design - Deep Python and backend automation experience - Proven fast learner with a track record of mastering new domains (AI, Quant) **❌ Missing Required:** NoSQL databases (Mongo), Hands-on AWS services (Lambda, ECS/EKS)

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a highly skilled Systems Architect in modern, distributed systems and AI infrastructure (Linux, Python, Docker). However, the role is for a Mainframe Infrastructure Architect, requiring a completely different and non-transferable technology stack (z/OS, JCL, Assembler, REXX). This is a critical domain gap that makes the candidate a poor fit despite their impressive technical aptitude and learning ability. **⚠️ Critical Gaps:** - The core requirement is Mainframe platform expertise (z/OS, JCL), while the candidate's entire background is in modern distributed/cloud infrastructure (Linux, Docker, Python). **✅ Strengths:** - Proven 'Fast Learner' with a track record of mastering complex new domains (AI Infra, Algo-trading). - Deep expertise in systems architecture and automation, albeit in a different technology stack. - Strong problem-solving and system design capabilities demonstrated by building a JIT system from scratch. **❌ Missing Required:** Experiencia como Analista de Suporte na plataforma Mainframe, Domínio de software básico IBM: z/OS (RACF, WLM, OMVS, JES3, TCPIP, VTAM, DFSMS, DFHSM e SMP/E), Programação em linguagens: Assembler, REXX e JCL, Atuação e customização de Sistema Operacional zOS

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Pro] The candidate is a strong Systems Architect with excellent foundational skills in Python, SQL, and DevOps, plus a proven ability to learn complex domains. However, there is a critical gap as they lack any hands-on experience with the core big data technologies required for this Data Architect role, such as Spark, Kafka, Flink, and modern data warehousing frameworks (dbt, Airflow). **⚠️ Critical Gaps:** - The candidate has no experience in the modern big data ecosystem (Spark, Kafka, Flink, etc.), which is the primary focus of this role. Their expertise is in building bespoke automated systems, not the large-scale data platforms described. **✅ Strengths:** - Strong Python and SQL proficiency with demonstrated application in complex systems. - Proven ability to architect and build resilient, automated systems from scratch. - Solid grasp of infrastructure-as-code (Terraform, Docker) and CI/CD principles. **❌ Missing Required:** Hands-on experience with Spark for data transformation., Experience with streaming architectures using Kafka or Flink., Proficiency with orchestration and modeling tools like dbt, AWS Glue, or Airflow., Experience building modern data architectures like data lakes or lakehouses., Significant experience developing data systems directly on a major cloud platform (AWS/GCP/Azure).

[ANALYSIS_REPORT] **WEAK_MATCH** [Copilot: gpt-5] Strong systems/infra and identity background, but lacks core cybersecurity/network security, SASE/SSE, Salesforce, and formal sales engineering experience; fast learner potential mitigates but immediate fit is limited. **⚠️ Critical Gaps:** - Cybersecurity (deep) - Network Security - SASE/Secure Service Edge - Salesforce CRM - Pre-sales/Sales Engineering experience **✅ Strengths:** - Technical acumen in systems/infra (Docker/Terraform/Linux) - Identity & access concepts (SSO/OIDC/SAML, RBAC) - Python automation & CI/CD useful for demos/POCs **❌ Missing Required:** Cybersecurity (deep), Network Security, SASE/Secure Service Edge, Salesforce CRM

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] O candidato é um Arquiteto de Soluções forte com vasta experiência em design de sistemas complexos e uma trajetória de carreira que o direciona para a área de dados. Embora não possua experiência direta com Oracle e AWS Redshift, que são centrais para a vaga, suas habilidades fundamentais em SQL, arquitetura de sistemas e capacidade comprovada de aprendizado rápido o tornam um candidato promissor que poderia se adaptar. **✅ Strengths:** - Systems Architecture Design - Proven Fast Learner & Self-starter - SQL & Database Fundamentals **❌ Missing Required:** Oracle databases, AWS Redshift, Data modeling tools (e.g., ERwin, Oracle SQL Developer), PL/SQL

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a skilled generalist Systems Architect with a strong background in custom infrastructure, Python, and AI. However, there is a complete and critical gap regarding the core technology required: SAP. The role is for a highly specialized SAP S/4HANA Utilities Architect, and the candidate's resume shows zero experience with SAP, IS-U, or regulated utility industry processes. **⚠️ Critical Gaps:** - The candidate has no experience in the SAP ecosystem, which is the fundamental requirement for this architect role. The entire job is centered around SAP S/4 Utilities, a technology not mentioned in the resume. **✅ Strengths:** - Strong systems architecture and integration skills in a non-SAP context - Proven ability to learn and implement complex technologies from scratch - Experience translating business needs (logistics, finance) into technical systems **❌ Missing Required:** Experiência como Arquiteto SAP IS-U / Utilities, Domínio do modelo S/4HANA Utilities, Domínio de processos críticos de Utilities, Conhecimento de SAP Activate e Fit-to-Standard

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: gpt-5] Strong systems/infrastructure and Python/SQL background with customer consulting; lacks explicit MongoDB/Atlas and cloud HA implementations but fast learner with AI and automation depth. **✅ Strengths:** - Python & SQL proficiency - Systems architecture and automation (metal-up) - Linux/Docker/Terraform infrastructure **❌ Missing Required:** Hands-on implementation of highly available cloud architectures, Production-grade MongoDB document data modeling

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a proven Systems Architect with impressive self-taught skills in AI infrastructure and automation, but possesses a critical and complete gap in the required SAP ecosystem. The role is exclusively focused on SAP integration (S/4HANA, Implico, CPI/PI-PO), of which the candidate has no demonstrated experience, making it a fundamental mismatch despite their architectural abilities. **⚠️ Critical Gaps:** - The core requirement is for an SAP Integration Architect, and the candidate has no background in the SAP technology stack (S/4HANA, CPI, PI/PO, etc.). **✅ Strengths:** - Strong generalist background in Systems Architecture and integration. - Proven ability to learn and implement complex technologies independently. - Transferable experience in Supply Chain and ERP-related projects. **❌ Missing Required:** Experiência comprovada como Arquiteto de Integração SAP, Vivência em projetos de implantação SAP S/4HANA (Greenfield), Conhecimento em integrações SAP (ex.: CPI, PI/PO, APIs, IDocs, OData)

[ANALYSIS_REPORT] **WEAK_MATCH** [Copilot: gpt-5-mini] Strong infrastructure and architecture background (Terraform, Linux, Docker, infra automation, system design) and demonstrated ability to self-host and optimize complex systems; however the role demands deep, hands-on Azure-specific experience (IaaS migrations, Bicep, Azure networking/security, Azure AD/managed identities, Azure monitoring/backup) that is not present on the resume. Candidate shows high fast‑learner potential and transferable IaC skills but several Azure-domain gaps are blocking for this role without ramp time. **⚠️ Critical Gaps:** - Hands-on Azure IaaS migration experience (lift-and-shift and virtual hosting) - BLOCKING - Bicep template development for Azure resources - BLOCKING - Azure networking & security patterns (NSG, VNet peering, routing, Azure Firewall) - BLOCKING **✅ Strengths:** - System architecture and end-to-end production deployments - Infrastructure automation (Terraform, CI/CD, scripting) and Linux expertise - Demonstrated self-starter with fast ramp on emerging technologies (self-hosted LLMs, custom infra) **❌ Missing Required:** 10+ years specifically focused on Azure infrastructure architecture (explicit Azure track record), Background in Azure IaaS migrations (lift-and-shift), Bicep expertise to design compute/network/storage/identity/security, Expertise with Azure AD/ADDS integration and managed identities, Familiarity with Azure monitoring, backup policies, update management

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: gpt-5-mini] Strong systems-architecture and integration background with proven delivery and infra skills; missing explicit production Azure experience and some cloud-native/microservices technologies but demonstrates fast-learning ability and relevant transferable skills. **⚠️ Critical Gaps:** - Microsoft Azure (lack of explicit production Azure experience) **✅ Strengths:** - End-to-end systems architecture and delivery (metal-up, production deployments) - API-driven integration and automation (procurement/WMS integrations, JIT systems) - Infrastructure & DevOps fundamentals (Terraform, Docker, Linux, CI/CD) and rapid self-directed learning **❌ Missing Required:** Azure cloud

[ANALYSIS_REPORT] **WEAK_MATCH** [Copilot: gpt-5-mini] Strong systems architecture, automation and data-engineering background with demonstrated fast-learning and infra skills, but lacks core, immediately required SAP migration tooling and enterprise RDBMS experience needed for this role. **⚠️ Critical Gaps:** - PowerCenter (Informatica) - SAP Migration Cockpit (LTMC) - Enterprise RDBMS experience (HANA / Oracle / SQL Server) **✅ Strengths:** - System architecture + automation: built production JIT inventory and integrated systems end-to-end - Hands-on infrastructure: Docker, Terraform, Linux, local GPU/LLM clusters and CI/CD pipelines - Data engineering + scripting: strong Python, SQL, pipeline automation and fast self-directed learning **❌ Missing Required:** Profundo conhecimento em PowerCenter (Informatica), Experiência com SAP Migration Cockpit (LTMC) / ferramentas ETL do ecossistema SAP, Familiaridade com SAP Activate e metodologias de migração, Sólida experiência prática em HANA, Oracle ou SQL Server (prod/optimização)

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] The candidate is a strong conceptual architect with a proven track record of building complex, automated systems from scratch. His expertise in IaC (Terraform), CI/CD, Python, and SQL is a direct match. However, the role requires deep, hands-on implementation experience with specific AWS data services (RDS/Aurora, Glue, Lambda), which the candidate only lists as "AWS Basics," creating a notable gap between his foundational strengths and the job's specific tooling requirements. **✅ Strengths:** - Deep expertise in Infrastructure-as-Code (Terraform) and CI/CD principles - Proven ability to architect and build entire automated data systems (JIT) - Strong Python and SQL skills applied in data-heavy environments (quant trading, logistics) **❌ Missing Required:** Experience implementing high availability solutions specifically on AWS, Experience with AWS data services (Glue, Lambda, RDS/Aurora), Expert-level understanding of data warehouses (Redshift, Snowflake)

[ANALYSIS_REPORT] **WEAK_MATCH** [Copilot: gpt-4.1] The candidate demonstrates strong experience in architecture, automation, cloud basics, and leadership, with proven ability to build complex, production-grade systems and lead technical initiatives. However, there are critical gaps in direct .NET/C# experience, deep Azure platform expertise, and Microsoft-specific DevOps tooling, which are central to the role. The candidate's fast learning and broad system integration background are strong positives, but the lack of hands-on .NET and Azure depth is a significant gap for this specific position. **⚠️ Critical Gaps:** - .NET/C# development and architecture - Deep Azure platform experience (beyond basics) **✅ Strengths:** - System architecture and automation - Cloud infrastructure (general, with Terraform/Docker) - Leadership and cross-functional communication **❌ Missing Required:** .NET, C#, Azure App Service, Azure Functions, Azure API Management, Azure Kubernetes Service, Azure Service Bus, Azure Key Vault, Azure Storage, Azure DevOps

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] The candidate is a strong systems architect with proven experience delivering complex, automated systems and possesses key skills like Python, Terraform, and SQL. However, there is a critical gap between their deep experience in self-hosted/local infrastructure and the job's explicit requirement for deep, production-level AWS expertise. While a fast learner, they lack the required hands-on proficiency with a wide range of AWS services and modern data platforms like Kafka or Spark. **⚠️ Critical Gaps:** - Deep, production-level AWS experience (candidate focus is on self-hosted/local infrastructure) **✅ Strengths:** - End-to-end systems architecture - Automation with Python and Terraform - Strong background translating business needs (ROI, resilience) to technical solutions **❌ Missing Required:** NoSQL, Hadoop, Spark, Kafka, Kinesis

[ANALYSIS_REPORT] **WEAK_MATCH** [Copilot: claude-sonnet-4.5] Strong foundational match with systems architecture experience and Python automation skills. The candidate demonstrates architecting complex systems (JIT inventory, AI infrastructure) and has AWS basics knowledge. However, lacks deep AWS service expertise, professional-level AWS certifications, and direct customer-facing consulting experience at enterprise scale. The 'fast learner' profile and systems thinking are evident, but this role requires immediate AWS depth. **⚠️ Critical Gaps:** - AWS certification (Preferred qualification - AWS Professional level) - Enterprise-scale customer consulting experience - Proven AWS cloud architecture delivery (3+ years required) **✅ Strengths:** - Strong systems architecture and end-to-end solution design (JIT inventory system) - Python scripting and automation expertise (matches 'scripting for automation' requirement) - Technical bridge role experience connecting business objectives to infrastructure solutions **❌ Missing Required:** 3+ years of cloud architecture implementation (has self-hosted/local, not enterprise cloud), 3+ years delivering cloud projects (AWS specifically not demonstrated)

[ANALYSIS_REPORT] **STRONG_MATCH** [Copilot: gpt-4.1] The candidate demonstrates strong experience in solution architecture, infrastructure, and technical leadership, with a proven track record in designing and implementing complex, integrated systems. Most core requirements—such as architecture design, POC execution, technical documentation, and strategic thinking—are well covered. The only notable gaps are specific tool experience (CRM, SharePoint, and possibly advanced architecture diagramming tools), but these are not critical blockers given the candidate's fast learning and broad technical foundation. **✅ Strengths:** - Solution architecture - Infrastructure and automation - Strategic and systems thinking **❌ Missing Required:** CRM tools, SharePoint

[ANALYSIS_REPORT] **DISQUALIFIED** [Copilot: claude-sonnet-4.5] Candidate shows strong foundational engineering and systems architecture skills with Python/SQL proficiency and CI/CD experience. However, this role requires deep Azure ecosystem expertise (8+ years with Databricks, Synapse, Data Factory) and big data technologies (Spark, Hadoop, PySpark) that are entirely absent from the resume. The candidate's experience is primarily in e-commerce automation, supply chain, and algorithmic trading - not enterprise data architecture. While demonstrating 'fast learner' potential through diverse projects, the 8+ years Azure/Databricks requirement and lack of any cloud data platform experience creates a critical experience gap. **⚠️ Critical Gaps:** - Zero experience with Azure cloud ecosystem (all core Azure services missing) - No big data technology experience (Spark/Hadoop/PySpark required but absent) - No Databricks experience whatsoever (primary platform for role) - 8+ years experience requirement vs candidate's profile showing adjacent but different domains - No enterprise data warehousing or data lake architecture background - Missing Power BI reporting experience (required for end-to-end solutions) **✅ Strengths:** - Strong Python programming with data libraries (Pandas/NumPy/PyTorch) - Proven systems architecture and automation design skills - SQL proficiency and CI/CD pipeline experience **❌ Missing Required:** Azure Databricks (cluster management, notebooks, Delta Lake), PySpark proficiency, Big data technologies (Hadoop, Spark), Azure Data Lake Storage, Azure Synapse Analytics, Azure Data Factory, Delta tables and Delta Lake, ETL/ELT processes at enterprise scale, Data warehousing architecture, NoSQL databases, Power BI development

[ANALYSIS_REPORT] **DISQUALIFIED** [Copilot: gpt-5-mini] Strong systems architecture and rapid-learning engineering background but lacks the core Oracle PSRM product, OUAF/Java development and domain-specific revenue/tax/collections experience required for an immediate senior PSRM role. **⚠️ Critical Gaps:** - Oracle PSRM (product experience) — blocking - OUAF development (framework-specific) — blocking - Java / J2EE for PSRM customizations — blocking - Oracle Inbound Web Services (integration) — blocking - Deep functional PSRM domain knowledge (tax/revenue/collections modules) — blocking **✅ Strengths:** - Architecting and delivering production automation and infrastructure - Strong scripting/engineering (Python) and data-handling experience - Practical experience operating Linux-based systems, containers and CI/CD **❌ Missing Required:** Practical experience with Oracle PSRM 2.2.0 or higher, Development experience on Oracle Utilities Application Framework (OUAF), Java / J2EE experience for PSRM extensions, Experience with Oracle Inbound Web Services integrations, Experience with PSRM Analytics, Parametrization/configuration experience for migrations (taxes/VAT/revenue/collections), Hands-on knowledge of the PSRM functional areas listed in the JD

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a highly capable systems architect with a proven ability to build complex, automated systems from the ground up. However, there is a critical and significant gap between their experience in custom/open-source stacks (Python, Docker, local AI) and the job's core requirement for deep expertise in the Oracle EPM/Hyperion ecosystem (PBCS, FCCS). While they are a strong technologist, they are a poor fit for the specific proprietary tools required by this role. **⚠️ Critical Gaps:** - The entire role is centered on the Oracle Enterprise Performance Management (EPM) suite, with which the candidate has no demonstrated experience. **✅ Strengths:** - Strong Systems Architecture & Automation skills - Expertise in Python for data and backend logic - Proven fast learner with a track record of self-teaching complex technologies **❌ Missing Required:** EPM Planning, Hyperion, Financial Consolidation (FCCS), PLSQL, Calc Script, Groovy, EPM Automate

[ANALYSIS_REPORT] **WEAK_MATCH** [Copilot: gpt-5] Strong systems/integration and supply chain background with fluent English; lacks direct SAP ECC + Brazilian tax integration and Kinaxis/Anaplan exposure, which are central to the role but likely learnable. **⚠️ Critical Gaps:** - Hands-on SAP ECC - Integration of Brazilian tax/fiscal reporting systems with SAP ECC - Kinaxis Maestro Integration Layer **✅ Strengths:** - Supply chain domain expertise (MITx MicroMasters + JIT systems) - Production-grade automation/APIs in Python - Fluent English and business-tech bridging **❌ Missing Required:** SAP ECC knowledge, Experience integrating Brazilian tax systems with SAP ECC

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] Candidate is a very strong technical architect, perfectly matching the role's requirements for designing implementation plans and handling API/SDK integrations. While technically proficient, there is a significant gap in the marketing/mobile domain, which is core to Braze's business. The candidate's proven ability to learn complex topics quickly mitigates this risk, making them a strong, but specialized, fit. **✅ Strengths:** - Solutions Architecture & System Design - API & Systems Integration - Proven Fast Learner in Complex Technical Fields **❌ Missing Required:** Marketing domain knowledge, Mobile domain knowledge

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: gpt-5-mini] Strong systems-architecture and hands-on infra + Python/ML experience matches many technical requirements and shows high 'fast learner' potential; gaps are primarily MongoDB-specific, enterprise pre-sales experience, and cloud-managed DB/deployment tooling which are learnable but important for this role. **⚠️ Critical Gaps:** - Enterprise Pre-Sales experience (5–7 years) — role expects seasoned pre-sales background - MongoDB-specific expertise (Atlas/core/migration/features) — core product knowledge expected **✅ Strengths:** - Proven systems architect with end-to-end production deployments - Strong Python + AI/ML (LLMs) and data tooling experience - Infrastructure & automation experience (Docker, Terraform, CI/CD, Linux) **❌ Missing Required:** 5–7 years of enterprise pre-sales experience (not evident in resume), Demonstrated MongoDB/Atlas experience (not found, cannot be inferred)

[ANALYSIS_REPORT] **WEAK_MATCH** [Copilot: claude-sonnet-4.5] Strong architectural foundation and automation expertise, but lacks the required 3+ years of hands-on production experience with AWS, Kubernetes, and Terraform. Candidate demonstrates 'fast learner' profile with proven ability to build complex systems from scratch (JIT inventory, AI clusters, trading bots). The infrastructure thinking is solid (Docker, Terraform basics, local clusters), but professional experience with enterprise-scale cloud platforms is limited. Advanced English requirement is met (bilingual). This is a skill-gap role, not a domain mismatch. **⚠️ Critical Gaps:** - Insufficient documented AWS production experience (has 'AWS Basics' vs. 3+ years required) - No demonstrated Kubernetes production experience (has Docker/local clusters) - Limited Terraform production track record (knows tool but lacks 3+ year requirement) **✅ Strengths:** - Strong systems architecture background with proven automation success (JIT system with >95% reliability) - Bilingual (Portuguese/English) - meets Advanced English requirement - Foundational cloud/IaC knowledge (Docker, Terraform, AWS Basics, Linux) with demonstrated learning velocity **❌ Missing Required:** 3+ years AWS production environment design/operation, 3+ years Kubernetes production cluster management, 3+ years Terraform IaC implementation, Proven large-scale cloud platform operations, High-availability enterprise systems experience

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Pro] The candidate is a strong systems architect with proven, hands-on experience in AI infrastructure, automation, and system integration. However, there is a critical gap in the required language stack (C++, Rust, .NET) and no experience with the mandatory ServiceNow platform, making them a high-risk fit for this specific role despite their impressive learning velocity. **⚠️ Critical Gaps:** - Required language stack: C++, Rust, and .NET. Candidate's experience is primarily in Python and shell scripting. **✅ Strengths:** - Deep, practical AI infrastructure experience (self-hosted LLMs) - Proven systems architecture and full-cycle automation skills - Demonstrated fast learner with a strong career trajectory towards complex systems **❌ Missing Required:** ServiceNow Integration, Cloud experience in Azure (candidate has AWS), 10+ years in roles focused purely on software engineering (candidate has ~7 years direct, with adjacent experience prior)

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: gpt-5-mini] Strong systems architecture, AI-infrastructure and automation background with DevOps tooling (Docker, Terraform, CI/CD) and fluent English; however lacks domain-specific Energy & Utilities experience and formal public/private bidding (RFP/RFI/RFQ/pregões) and SAP/Billing/CRM bid experience which are central to the role. **⚠️ Critical Gaps:** - Energy & Utilities domain expertise (regulatory/operational knowledge) - BLOCKING - Hands-on experience managing formal procurement/bid processes (RFP/RFI/RFQ/pregões) - BLOCKING - Experience running SAP/Billing/CRM bids or implementations (commercial/technical scoping) - BLOCKING **✅ Strengths:** - Systems architecture & metal-up AI infrastructure (local LLM clusters) - Automation and engineering to production: Python, CI/CD, Terraform, Docker - Business-aligned solutions with ROI focus (supply chain + finance experience) **❌ Missing Required:** Proven track record in Energy & Utilities projects (saneamento, power, Oil&Gas) not present, Demonstrable experience with RFP/RFI/RFQ and pregões eletrônicos processes, Specific experience leading bids for SAP, Billing or CRM solutions

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: gpt-4.1] The candidate demonstrates strong expertise in Python, Terraform, SQL, Docker, and infrastructure automation, with proven experience building complex, production-grade systems and pipelines. However, there are notable gaps in direct, advanced AWS data services (Glue, Redshift, EMR, Athena, DynamoDB), Apache Spark, Airflow, Kubernetes (EKS), and AWS certification. The candidate's fast learning ability and broad technical foundation suggest high adaptability, but the absence of hands-on experience with several core AWS data tools and distributed data processing frameworks is a significant gap for this specialized Data Architect role. **⚠️ Critical Gaps:** - Apache Spark - Airflow - Kubernetes (EKS) - AWS Glue/Redshift/EMR (hands-on, not just basic AWS) **✅ Strengths:** - Python and automation expertise - Infrastructure as Code (Terraform, Docker, Linux) - Proven ability to architect and deliver complex, resilient systems **❌ Missing Required:** Hands-on experience with AWS Glue, Redshift, EMR, Athena, DynamoDB, Apache Spark, Airflow, Kubernetes (EKS), AWS Certification

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: gpt-5] Strong systems/architecture and integration background with fluent English; gaps in Java, microservices, NoSQL, and advanced public cloud depth. Fast learner with proven end-to-end delivery suggests ramp-up viability. **⚠️ Critical Gaps:** - Production-grade Java - Advanced public cloud architecture (AWS/Azure/GCP) - Microservices architecture design **✅ Strengths:** - Systems integration & automation - Python/SQL data engineering - Security/Identity & DevOps (SSO/RBAC, Docker/Terraform) **❌ Missing Required:** Java, Microservices, NoSQL, Advanced Public Cloud (AWS/Azure/GCP)