Python ⏐ SQL ⏐ GCP ⏐ Azure ⏐ Airflow ⏐ BigQuery ⏐ Data Factory ⏐ Git
I'm a Data Engineer with 4 years of experience, but I started my career as an Academic Monitor.
I've worked on projects for major companies like PUC Minas, Spotify (BR, LATAM), Heineken, 99, Itaú, Vale,
Mercado Livre, MSD/Merck (Global)… all involving architecture, automation, ETLs & analysis.
Since I started my career, I've been into open-source projects, studying cloud
architectures (GCP, Azure) and tech such as Python, SQL, Airflow, Data Factory, MongoDB, PostgreSQL.
I truly enjoy planning projects, making them scalable, discussing and understanding how the project
achieves the company's goals.
Outside of work, I like to share experiences:
🖊️ Medium → Data insights
📺 YouTube → Academic projects
🧑💻 GitHub → Study + Open-Source projects
Right now, I'm actively exploring roles in high-performance projects, automation, and robust architectures.
Predicting the effectiveness of election campaigns
Faça um reforço um monitor universitário certificado
Get public data from Instagram easily and quickly
A professional toolkit for workflow optimization
All projects developed at Computer Science
All projects developed at Computer Engineering
Specialized in resolving structural complexities and eliminating technical debt through solid foundations.
Architecting and deploying high-scale ETL pipelines and multi-cloud infrastructure (GCP/Azure) to ensure high availability for critical projects.
Enforcing LGPD compliance and governance frameworks through comprehensive technical documentation, data mapping, and security protocols.
Developing proprietary Python libraries and standardized scaffolding to reduce MVP development time and automate data ingestion workflows.
Integrating AI solutions and NLP bots into internal workflows while leading agile methodology adoption for streamlined project scalability.
I establish engineering departments from the ground up and implement scalable architectures. By developing internal libraries and standardizing code, I reduce development time and streamline the onboarding of new technical staff.
I architect high-scale ETL pipelines to automate data ingestion and analysis for major global brands like Spotify and Heineken. To maintain reliability, I build 24/7 monitoring ecosystems that ensure high availability and minimize maintenance hours for critical projects.
I integrate AI solutions and NLP bots into existing workflows to automate customer service and data queries. I also develop specialized toolkits, such as QUATI, to automate repetitive engineering tasks and accelerate the delivery of data solutions.
I manage multi-cloud infrastructure while enforcing strict information security policies. This includes ensuring compliance with data protection laws like LGPD through technical documentation, data mapping, and security protocols.
I have extensive experience managing multi-cloud infrastructure, specifically GCP and Azure. I implement standardization policies across these environments to ensure consistency, information security, and seamless data integration.
I specialize in using Airflow and Python to orchestrate complex data workflows. My expertise includes managing databases like BigQuery, SQL Server, and Oracle, ensuring efficient data lifecycles and robust DataOps practices.
Absolutely. I have built ETL pipelines to automate data ingestion from platforms like Facebook, Instagram, TikTok, and Twitter. My work often involves competitive analysis and performance insights for brands operating in the digital space.
Yes, I develop comprehensive DataViz solutions using Microsoft Power BI and Looker Studio. I also engineer health monitors and 24/7 monitoring ecosystems to ensure that BI dashboards remain accurate and highly available for stakeholders.
Send me an email and we can discuss about your project. ;-)