* BIX Teach is the USA office of BIX Tecnologia (headquarters office).Building data architectures from solutions architecture proposals to deployment implementation and daily maintenance. Currently focused on cloud environments in AWS and GCP. Utilizing modern technologies such as DataOps (CI/CD pipelines with GitHub Actions) and Infrastructure as Code with Terraform. Experienced in data platforms, data warehousing, and lakehouse solutions including BigQuery, Athena, and… Show more * BIX Teach is the USA office of BIX Tecnologia (headquarters office).Building data architectures from solutions architecture proposals to deployment implementation and daily maintenance. Currently focused on cloud environments in AWS and GCP. Utilizing modern technologies such as DataOps (CI/CD pipelines with GitHub Actions) and Infrastructure as Code with Terraform. Experienced in data platforms, data warehousing, and lakehouse solutions including BigQuery, Athena, and Databricks.Current AWS Project: SaaS platform (for a North American customer, project conducted in English)Context: Deploying a SaaS solution based on AWS managed services for processing sensitive information and personal documents.Technologies and Actions: Managing all infrastructure using Terraform and GitHub Actions to deploy and control multiple services such as ECS, DynamoDB, API Gateway, Amplify, CloudWatch, Kinesis, Eventbridge, IAM, and others.Role: Serving as an Architect/DevOps engineer and focus on FinOps and cost management, managing user access using IAM, MFA, roles, policies and groups management, implementing AWS Organizations for multiple environments, and utilizing GitHub Actions and Terraform for automation. Show less

Highlights projects:• Academic Data Warehouse: On-premise architecture for migrating a legacy Postgres DW to a new one. Challenges: Legacy DW is complex with significant data duplication, resistance to a cloud environment, and network conflicts between container IPs and VPN access.Stack: Python/SQL, Airflow, Grafana, Prometheus, Git Actions (SEMVER, branches patterns) and Docker.• People Analytics: Through the lack of employee data integration, by several sources, such as:… Show more Highlights projects:• Academic Data Warehouse: On-premise architecture for migrating a legacy Postgres DW to a new one. Challenges: Legacy DW is complex with significant data duplication, resistance to a cloud environment, and network conflicts between container IPs and VPN access.Stack: Python/SQL, Airflow, Grafana, Prometheus, Git Actions (SEMVER, branches patterns) and Docker.• People Analytics: Through the lack of employee data integration, by several sources, such as: candidates and job applications, ERPs, finance, HR, payroll and people management, I've built a lambda architecture on GCP to deliver the data in Bigquery.Serverless Event Driven: API Gateway, Pub/Sub and Cloud Functions; Compliance and PII: IAM, Data Catalog Policy Tags and Bigquery row-level security; Processing: Kubernetes Engine, Bigquery, Python and SQL; Orchestration: Airflow (Composer). • Customer Data Platform: Integrated CRM data warehouse (BigQuery) with the VTEX e-commerce and CDP platform, enabling the activation and deactivation of marketing and CRM campaigns. This includes campaigns for individuals celebrating their birthdays, brand anniversaries, and anti-churn strategies (triggered before each 90-day period without an invoice).Integration: Postman, API Gateway, Pub/Sub and REST APIs; Processing: Python (Polars) and Bigquery;Orchestration: Airflow (Composer).• Marketing Analytics: Developed architecture for consuming events from platforms such as Google Ad Manager, Google AdSense, and Facebook Ads Manager. Executed the migration from MySQL to BigQuery, implementing best practices like partitioned tables and clustered keys. Additionally, integrated Airflow failed alerts into a Discord channel. Stack: Apache Airflow, MySQL, API REST and Bigquery. Show less

Highlight Projects: • "Commercial Performance" Project, Retail in General: Delivery of sales base and stock data (daily photos). Key Metrics: Sales [Revenue, Same Store Sale, and Channel], Stock [In Transit, Out of Stock]. With this data, various analyses became possible: commercial performance, out-of-stock calculation, and stock position. Sales updates went from once a day to once every 2 hours. • "Sales Funnel" Project, B2B: Integration of Sales Funnel data between On-Premise… Show more Highlight Projects: • "Commercial Performance" Project, Retail in General: Delivery of sales base and stock data (daily photos). Key Metrics: Sales [Revenue, Same Store Sale, and Channel], Stock [In Transit, Out of Stock]. With this data, various analyses became possible: commercial performance, out-of-stock calculation, and stock position. Sales updates went from once a day to once every 2 hours. • "Sales Funnel" Project, B2B: Integration of Sales Funnel data between On-Premise Server (SQL-Server) with Google Cloud and Salesforce. Data includes: Customer prospecting, business opportunities, customers, and sales. • "Customer Base" Project, CRM: Improvement in the historical email database, creation of attributes [favorite_customer, favorite_store, favorite_salesperson, favorite_brand, among others], and implementation of the salesperson database.Technologies and Tools: • Google Cloud (BigQuery, Cloud Storage, Cloud Functions, Cloud Scheduler, Cloud SQL, Cloud Composer, Kubernetes Engine, Data Catalog) • Python • SQL • PySpark • Delta Lake • Airflow • Git Actions Show less

Some of the topics discussed on our episodes: • Recommendations for Agile tools for your project; • Why should you use Git and Github?; • Our experience at university and what it comes after that; • The Python language versatility.Podcast created among friends, with intention of to do networking on our social mediaSpotify: https://open.spotify.com/show/71nUSUgO1cAXOvMQb9zJy1?si=b8df7f2a0b6e44fcYouTube:… Show more Some of the topics discussed on our episodes: • Recommendations for Agile tools for your project; • Why should you use Git and Github?; • Our experience at university and what it comes after that; • The Python language versatility.Podcast created among friends, with intention of to do networking on our social mediaSpotify: https://open.spotify.com/show/71nUSUgO1cAXOvMQb9zJy1?si=b8df7f2a0b6e44fcYouTube: https://www.youtube.com/channel/UCIWSZzXA145nGI77QnNrkfg/videos Show less

• Coordenação de atendimento do CEMAS (Centro De Especialidades Medicas ) e de Unidades de Saúde da Família (USAFA), assim como orientações sobre o fluxo de atendimento;• Relatório de melhorias e verificação de qualidade de serviço.

Poupatempo Litoral Consortium - Beachfront Service Centers in Praia Grande and São VicenteIT Technician Level I• Management and support of all hardware, systems, and other devices at Poupatempo Praia Grande/São Vicente;• Installation and configuration of IP printers by network segmentation, installation and configuration of biometric devices;• Implementation of training plans for Poupatempo system users, as well as other government agencies, Detran, and IIRGD;• Technical… Show more Poupatempo Litoral Consortium - Beachfront Service Centers in Praia Grande and São VicenteIT Technician Level I• Management and support of all hardware, systems, and other devices at Poupatempo Praia Grande/São Vicente;• Installation and configuration of IP printers by network segmentation, installation and configuration of biometric devices;• Implementation of training plans for Poupatempo system users, as well as other government agencies, Detran, and IIRGD;• Technical point of contact for incident management with PRODESP. Show less

• Citizen service;• Guidance and verification of documentation, as well as procedures for DETRAN and IIRGD services.