Anti-ATS Evaluatorv1.3

[ANALYSIS_REPORT] **LOW** [Opencode: opus-4-6] This role requires proficiency in Java (Spring Boot), extensive AWS Cloud experience (EC2, S3, Lambda, API Gateway), Docker/Kubernetes, and REST API architecture. The candidate has Docker, basic AWS knowledge, CI/CD concepts, and API experience, but completely lacks Java/Spring Boot — the core language requirement. The enterprise banking context (Porto Bank) with Scrum/Kanban methodology and hybrid São Paulo work model further reduces fit. **Strengths:** Docker experience, CI/CD concepts, API development experience, Financial domain background **Critical Gaps:** Java (Spring Boot) — primary language requirement **Missing Required:** Java (Spring Boot), Kubernetes, REST/RESTful architecture at enterprise scale, GitLab/Jenkins

[ANALYSIS_REPORT] **LOW** [Opencode: opus-4-6] The candidate has Python familiarity and SQL knowledge, which match two requirements. However, the role demands solid experience with GCP (BigQuery, Cloud Storage, Dataflow, Composer) and AWS (S3, Redshift, Glue, Athena, Lambda), data modeling for Data Lake/Warehouse, and Airflow orchestration — all areas where the candidate has minimal or no demonstrated experience. The candidate's basic AWS knowledge and SQL provide some overlap, but the cloud platform depth required is far beyond what's demonstrated. **Strengths:** Python experience, SQL/PostgreSQL knowledge, English C2 fluent (technical English sufficient) **Missing Required:** GCP platform expertise, AWS advanced data services, Data modeling (Data Lake/Warehouse), Pipeline orchestration (Airflow)

[ANALYSIS_REPORT] **MEDIUM** [Opencode: opus-4-6] Strong overlap: Python (required, candidate has it), SQL (required, candidate has it), Docker (required, candidate has it), Git (required, candidate has it), FastAPI (candidate has API development but not specifically FastAPI — adjacent). The candidate's production API work with Go and experience building backend systems demonstrate relevant capabilities. However, the JD requires 'Superior completo em Ciência/Engenharia da Computação' which Mechatronics Engineering may not pass ATS filters, and 2 years of specific backend development experience with a 'Software Engineer' title is expected. **Strengths:** Python proficiency, SQL/PostgreSQL strong match, Docker experience, API development demonstrated in production, Financial domain background (fintech differential), Git and deployment experience **Missing Required:** FastAPI (core requirement, candidate has API experience but not FastAPI), CS/Computer Engineering degree (has Mechatronics — ATS may not match)

[ANALYSIS_REPORT] **MEDIUM** [Copilot: GPT5-mini] Senior Data Engineer for high-scale GraphQL & streaming APIs expects deep GraphQL and JavaScript/TypeScript/Node experience; candidate has JS/Node skills, PostgreSQL experience and data pipeline work but limited explicit GraphQL/federation or TypeScript usage. ATS sees adjacent strengths but notes missing GraphQL specialization. **Strengths:** Node.js and PostgreSQL experience, Data ingestion and pipeline knowledge, Observability and CI/CD familiarity

[ANALYSIS_REPORT] **LOW** [Opencode: sonnet-4-5] ATS heavily penalizes missing C#/.NET expertise, Azure DevOps pipeline experience, and 5+ professional software engineering years. The candidate has systems thinking, Go/Python backend skills, and CI/CD concepts, but ATS cannot infer C# proficiency from Go, and job titles (Financial Analyst, Supply Chain Planner) do not match 'Senior Software Engineer'. No inference pathway exists for .NET ecosystem. **Strengths:** Backend systems design, CI/CD pipeline concepts, Python proficiency **Critical Gaps:** No C#/.NET experience, No professional Software Engineer title, No Azure-specific experience **Missing Required:** 5+ years as Senior Software Engineer, C# / .NET proficiency, Azure Cloud Services hands-on experience

[ANALYSIS_REPORT] **LOW** [Opencode: sonnet-4-5] This is a mainframe CICS System Programmer role requiring deep legacy IBM mainframe expertise (CICS transaction server, z/OS, VSAM, RACF, SMP/E, REXX). The candidate has zero mainframe experience and comes from a modern cloud/automation/web systems background. This is a completely different technology domain with no transferable skills. **Critical Gaps:** Zero mainframe experience, Completely different technology domain **Missing Required:** CICS system programming experience, z/OS knowledge, CICS transaction server experience

[ANALYSIS_REPORT] **LOW** [Opencode: opus-4-6] This role requires deep expertise in AWS and Azure cloud architectures, specific migration tools (AWS DMS, AWS SCT), Aurora PostgreSQL, Azure SQL, and Terraform. The candidate has PostgreSQL experience and basic AWS knowledge, but lacks all migration-specific tools, Azure experience entirely, and Terraform expertise. This is a highly specialized data architecture migration role that requires certifiable cloud platform depth. **Strengths:** PostgreSQL experience, Basic AWS knowledge, English C2 (advanced English differential) **Critical Gaps:** AWS/Azure migration tooling (DMS, SCT), Azure platform expertise **Missing Required:** AWS DMS, AWS SCT, Azure SQL expertise, Terraform, Cloud migration architecture experience

[ANALYSIS_REPORT] **LOW** [Opencode: opus-4-6] The role requires deep Python experience, Apache Iceberg/Delta (imprescindível), AWS cloud services (S3, EC2, ECS, Athena, Glue), relational databases, and in-memory data processing. The candidate has Python and SQL/PostgreSQL experience, but completely lacks Apache Iceberg/Delta (marked as essential), advanced AWS data services, and PySpark. Additionally, the role requires presencial work in São Paulo (Itaim Bibi) and advanced/fluent English. **Strengths:** Python experience, SQL/PostgreSQL, English C2 fluent (matches requirement) **Critical Gaps:** Apache Iceberg or Delta (marked as 'imprescindível' — essential) **Missing Required:** Apache Iceberg/Delta, AWS advanced data services (Glue, Athena, ECS), In-memory data processing, Distributed data environments experience

[ANALYSIS_REPORT] **LOW** [Opencode: opus-4-6] The candidate has Python (partial match via scripting), some automation experience, and general process knowledge. However, this is a highly specialized role requiring 3+ years of experience specifically with CA Workload Automation (CAWA) — an enterprise workload scheduling tool. The candidate has no CAWA experience and no enterprise workload automation platform experience. The degree requirement in IT/CS may also not match Mechatronics Engineering in the ATS. **Strengths:** Python/Bash scripting, Database experience, Analytical problem-solving capability **Critical Gaps:** CA Workload Automation (CAWA) — completely different domain of automation **Missing Required:** CAWA platform expertise (3+ years), IT/CS degree

[ANALYSIS_REPORT] **LOW** [Opencode: opus-4-6] This is a C# .NET fullstack role requiring .NET 9.0, React, TypeScript, Entity Framework Core, Clean Architecture, DDD, and xUnit testing. The candidate has JavaScript experience but no C#/.NET, no React, no TypeScript, and no Entity Framework experience. The tech stack is completely mismatched. The only positive is the ERP knowledge differential, but it cannot compensate for the core stack gap. **Strengths:** ERP experience (TOTVS — matches differential), Git workflow experience, Remote work experience **Critical Gaps:** C# .NET ecosystem (entirely different stack), React/TypeScript frontend **Missing Required:** .NET 9.0, React, TypeScript, Entity Framework Core, Unit testing in .NET

[ANALYSIS_REPORT] **MEDIUM** [Opencode: sonnet-4-5] Strong match on database technologies, data modeling, system integration, Python, and consulting mindset. The candidate demonstrates hands-on database work (PostgreSQL, SQLite), API development, data pipeline design, and complex project delivery. However, missing direct Neo4j graph database experience and formal 5+ years in 'Software Engineer' title. ATS will dock points for missing graph DB expertise and professional SE years, but strong inference from data architecture work. **Strengths:** Database architecture and data modeling, PostgreSQL expertise, Python and API development, Consulting and advisory experience, Complex system integration, Docker and cloud fundamentals **Missing Required:** 5+ years designing enterprise-class applications with SE title, Neo4j or graph database experience

[ANALYSIS_REPORT] **MEDIUM** [Opencode: sonnet-4-5] Strong alignment on AWS fundamentals, Docker, Python, infrastructure thinking, and automation mindset. The candidate built production orchestration systems, managed containerized environments, and understands CI/CD pipeline design. However, missing formal Kubernetes production experience, Terraform/IaC tooling, and GitHub Actions/Jenkins. ATS infers DevOps capabilities from systems architecture and automation projects, but lack of 'DevOps Engineer' or 'Software Engineer' title hurts. **Strengths:** AWS fundamentals, Docker and containerization, Python for automation and tooling, Infrastructure design and optimization, CI/CD pipeline concepts, Systems thinking and orchestration **Missing Required:** 5+ years professional DevOps Engineering experience, Kubernetes production cluster management, Terraform hands-on experience

[ANALYSIS_REPORT] **LOW** [Opencode: opus-4-6] This role requires hands-on Earnix platform experience (implantation, development, or technical support) — a niche pricing/decision platform used in insurance. The candidate has no Earnix experience, no Java background, and no insurance/pricing system experience. While there's some overlap in SQL, API integration, and Git, the Earnix platform expertise is the non-negotiable core requirement. **Strengths:** SQL knowledge, API integration experience, Git versioning, Financial domain background (adjacent to insurance) **Critical Gaps:** Earnix platform experience — core and non-negotiable requirement **Missing Required:** Earnix practical experience, Enterprise software development background

[ANALYSIS_REPORT] **MEDIUM** [Opencode: sonnet-4-5] Good match on CI/CD concepts, Docker, AWS fundamentals, infrastructure design, and independent work. The candidate demonstrates platform engineering mindset through production deployments and automation. However, missing formal Kubernetes experience and professional 'DevOps/Platform Engineer' title. The hourly contract structure and 'strong communication' emphasis align well with consulting background. **Strengths:** CI/CD pipeline design concepts, Docker containerization, AWS infrastructure, Independent remote work, Platform reliability thinking, Strong communication skills **Missing Required:** Strong DevOps/Platform Engineer experience (title), Kubernetes hands-on experience

[ANALYSIS_REPORT] **LOW** [Opencode: sonnet-4-5] The candidate has strong systems thinking, Python/SQL proficiency, data pipeline concepts, and consulting experience. However, this Principal-level role requires 10+ years as Solutions Architect/Data Engineering leader, 2+ years consulting leadership, deep Snowflake expertise, and proven revenue generation for enterprise clients. The candidate lacks professional data engineering title, Snowflake hands-on experience, and leadership of distributed data engineering teams. Critical seniority and experience gaps exist. **Strengths:** Systems architecture thinking, Python and SQL proficiency, Data pipeline concepts, Consulting and client-facing experience, Cross-functional collaboration **Critical Gaps:** No 10+ years as Solutions Architect/Data Engineering leader, No 2+ years consulting leadership with external clients, No Snowflake hands-on experience, No proven revenue generation for enterprise clients, No experience managing Data Engineers/Solution Architects **Missing Required:** 10+ years Solutions Architect/Data Engineering leader, 2+ years consulting leadership, Snowflake expertise, Managing distributed Data Engineering teams, Revenue generation experience

[ANALYSIS_REPORT] **LOW** [Opencode: opus-4-6] The candidate has Python and SQL experience, which match two core requirements. Engineering degree (Mechatronics) matches 'Engenharias' in the education requirement. However, the role requires solid experience with PySpark, Databricks/Lakehouse, cloud data platforms, and data pipeline development at scale — all areas where the candidate has minimal demonstrated experience. The SaaS/high-growth differential is not matched. **Strengths:** Python practical experience, SQL/PostgreSQL, Engineering degree matches 'Engenharias' requirement, Proactive ownership mentality matches cultural fit **Missing Required:** PySpark, Databricks or equivalent Lakehouse platform, Cloud data platform experience at scale

[ANALYSIS_REPORT] **LOW** [Opencode: opus-4-6] The candidate has basic SQL and Python scripting ability, but this senior data engineering role at Stefanini (large consulting firm, 38k employees) specifically requires PySpark, AWS S3, and Iceberg/Parquet table experience. The candidate has PostgreSQL (adjacent to SQL) and basic AWS knowledge but lacks PySpark entirely and has no experience with Iceberg or Parquet file formats. The consulting context and DevOps pipeline requirement add further gaps. **Strengths:** SQL knowledge, Python baseline, Basic AWS familiarity **Missing Required:** PySpark, AWS S3 administration, Iceberg tables, Parquet file format

[ANALYSIS_REPORT] **LOW** [Opencode: opus-4-6] The candidate has Python, Docker, Git, CI/CD concepts, and PostgreSQL. However, this role demands deep expertise in Apache Spark/PySpark (described as 'destaque absoluto'), Airflow/Prefect orchestration, Databricks/Snowflake, AWS/GCP services (Glue, BigQuery, Dataflow), and Kafka/Fivetran streaming. The candidate also lacks recommendation systems experience which is listed as 'indispensável' (essential). The sheer volume of missing hard skills is overwhelming. **Strengths:** Python experience, Docker containerization, Git and CI/CD, English/Spanish requirement partially met (English C2) **Critical Gaps:** Apache Spark/PySpark (described as absolute priority), Recommendation systems experience (described as indispensável) **Missing Required:** Apache Spark/PySpark, Airflow/Prefect orchestration, Databricks or Snowflake, BigQuery, Recommendation systems

[ANALYSIS_REPORT] **LOW** [Opencode: sonnet-4-5] Moderate match on Python, SQL, data pipelines, and data modeling concepts. The candidate demonstrates data architecture thinking through ERP data remediation and inventory system design. However, missing professional Data Engineer title, PySpark/Scala, cloud platforms (AWS/Azure/GCP data services), and CI/CD implementation. ATS infers some data engineering skills from supply chain analytics and automation projects, but lack of formal big data tooling experience hurts. **Strengths:** Python proficiency, SQL and data modeling, Data quality and validation logic, Data pipeline concepts, PostgreSQL database design **Critical Gaps:** No professional Data Engineer title **Missing Required:** Degree in Computer Science/Engineering (has Mechatronics - ATS may not recognize equivalence), Data Engineer professional experience

[ANALYSIS_REPORT] **LOW** [Opencode: opus-4-6] This role is entirely Azure-focused: Data Factory, Synapse Analytics, Databricks, Data Lake, SQL Database. The candidate has zero Azure experience, no Databricks, no Synapse, and no Data Factory expertise. The only overlap is general SQL and the requirement for advanced English (candidate has C2). The role also requires hybrid presence and international stakeholder collaboration. **Strengths:** English C2 fluent (advanced English required), SQL knowledge baseline **Critical Gaps:** Microsoft Azure platform (entire role is Azure-focused) **Missing Required:** Microsoft Azure and all its components, Databricks, ETL/ELT pipeline construction, Data modeling

[ANALYSIS_REPORT] **LOW** [Opencode: sonnet-4-5] Minimal match on data architecture concepts and SQL. The candidate has data modeling experience from supply chain work, but this Principal-level SAP Analytics & Data Architect role requires deep expertise in SAP BDC, Datasphere, Databricks, Snowflake, and 10-15+ years in data architecture/engineering roles. Missing all SAP-specific platforms, modern data platform hands-on experience, and professional data architecture title. Critical seniority and technology gaps. **Strengths:** Data modeling concepts, SQL, Business-technical translation **Critical Gaps:** No SAP platform experience, No 10-15+ years data architecture/engineering experience, No modern data platform hands-on experience, No professional Data Architect title **Missing Required:** 10-15+ years data architecture/engineering/analytics experience, SAP BDC/Datasphere/SAC/BW/4HANA/HANA Cloud knowledge, Databricks/Snowflake/BigQuery hands-on experience, Customer-facing delivery projects, CS/Engineering degree (has Mechatronics - ATS may not recognize)

[ANALYSIS_REPORT] **LOW** [Opencode: sonnet-4-5] Moderate match on SQL, data modeling, ETL concepts, and data quality thinking. The candidate demonstrates data pipeline design through inventory automation and data remediation projects. However, missing Azure Data Factory, Databricks, Azure Data Lake, Delta Lake, and professional Data Engineer title. The onsite requirement (4 days/week in São Paulo) is feasible but adds friction. This is a 3-month contract role. **Strengths:** SQL and data modeling, Data quality and governance thinking, Data pipeline concepts, Problem-solving skills **Critical Gaps:** No Azure platform experience, No professional Data Engineer title **Missing Required:** Azure Data Factory expertise, Databricks expertise, Azure data services hands-on experience, Data Engineer professional experience

[ANALYSIS_REPORT] **LOW** [Opencode: opus-4-6] The candidate has Python, SQL, PostgreSQL, CI/CD concepts, and infrastructure awareness. However, the role requires mandatory Databricks experience (including Spark, Delta Lake, job optimization), advanced AWS services (S3, Glue, IAM, Lambda), and Lakehouse architecture expertise. The candidate has basic AWS knowledge and Python but lacks the specific platform depth required. Education requirement ('cursos de tecnologia — Engenharia, Computação, Sistemas') may accept Mechatronics Engineering. **Strengths:** Python experience, SQL/PostgreSQL, CI/CD awareness, Engineering degree may match requirement, Infrastructure and systems thinking **Missing Required:** Databricks (explicitly mandatory), Spark job optimization, Delta Lake, AWS advanced services for big data, Lakehouse architecture

[ANALYSIS_REPORT] **LOW** [Opencode: opus-4-6] The candidate has Python, SQL, and basic cloud knowledge. However, EY requires solid GCP experience (BigQuery is essential, Cloud Storage, Composer/Airflow), Databricks, data modeling, and advanced English. The candidate has English C2 (strong match) and Python/SQL baseline but lacks all GCP services, BigQuery, Databricks, and Airflow experience. The presencial São Paulo requirement with travel (15-25%) adds logistics constraints. **Strengths:** English C2 fluent (advanced English required), Python experience, SQL/PostgreSQL knowledge, Graduation completed **Missing Required:** BigQuery (essential), GCP platform, Databricks, Data modeling, Data pipeline construction at scale

[ANALYSIS_REPORT] **LOW** [Opencode: opus-4-6] The candidate has Python, SQL, AWS basic knowledge, and Terraform is unfamiliar. This Tech Lead role requires proven technical leadership of data engineering teams, deep expertise in Apache Iceberg, AWS (EC2, Glue, Athena, DataZone, Lake Formation), Airflow, Terraform, DBT, Prometheus/Grafana, and advanced English. The candidate lacks nearly all specific tools and has no data engineering team leadership experience. The API design knowledge is a minor positive. **Strengths:** Python and SQL, API design knowledge, English C2 fluent (matches advanced English requirement), Systems architecture thinking **Missing Required:** Apache Iceberg, AWS advanced data services, Airflow, Terraform, DBT, Technical team leadership experience, Advanced English in conversation