Domain understanding
I study the operational context before translating requirements into data models, APIs and interfaces.
AGRONOMY · BACKEND · DATA
Hi, I’m Arleu Júnior.
Agronomy undergraduate at UFV
I connect field knowledge with software engineering to build APIs, data-processing workflows and experimental AgTech systems using Python, SQL, FastAPI and PostgreSQL.
Open to internship and junior opportunities
- Python
- SQL
- FastAPI
- PostgreSQL
- Docker
CURRENT FOCUS
Backend + Data
Applied to agriculture
BASED IN
Viçosa, Brazil
UFV · Agronomy
01 · ABOUT
Field context translated into software.
My strongest advantage is not claiming to know every technology. It is combining an agricultural background with growing backend and data skills.
I am a final-year Agronomy undergraduate at the Federal University of Viçosa and an early-career developer focused on backend systems and data.
My background helps me understand field operations, business rules and the contexts in which operational data is generated. I use that perspective to develop projects involving APIs, databases, automation, telemetry and data validation.
My primary stack includes Python, SQL, FastAPI and PostgreSQL. I also use Docker, Git, automated tests and continuous integration to make projects easier to reproduce and maintain.
One of my main initiatives is AgriSentry, an experimental portfolio ecosystem created to explore agricultural telemetry ingestion, asynchronous processing and data-quality rules. It is a learning and engineering project—not a production platform.
I am seeking an internship or junior opportunity where I can contribute to real projects, participate in code reviews and continue building solid technical foundations with an experienced team.
Evidence over buzzwords
Projects are described according to what is implemented, tested and documented—not according to what sounds more senior.
Continuous improvement
I treat each project as a place to strengthen code quality, testing, data reliability and technical communication.
02 · EXPERIENCE
Agricultural operations, research and applied technology.
My professional experience began in agronomy. Software and data became tools for understanding processes and reducing repetitive work.
Pif Paf Alimentos Field Production & Data Intern 2025–2026
- Monitored commercial poultry operations with the technical coordination team, collecting field information related to biosecurity, housing preparation and flock conditions.
- Supported biological sampling, field necropsies and preslaughter visual assessments used in routine operational monitoring.
- Developed an experimental poultry-weight analysis prototype with Python, Pandas, Streamlit and XGBoost to explore data preparation, validation and forecasting workflows.
- Participated in technical meetings and connected field observations with opportunities for better data organization and analysis.
Scope note: the prediction application was an experimental prototype, not a production decision-making system.
ADWA Cannabis Field Data & Operations Intern 2022–2025
- Recorded environmental and crop variables in protected cultivation facilities and forest nurseries.
- Supported vegetative propagation, fertilization, phytosanitary management, harvest and post-harvest activities.
- Organized production records to improve traceability and consistency across recurring operational routines.
- Assisted with data collection and organization for applied agronomic research.
GeCotton — Cotton Study Group Events Assessor 2025–Present
- Support technical and scientific events focused on cotton, agricultural machinery and technology transfer.
- Developed Nomino, a tool that automates certificate generation from spreadsheet records and reduces repetitive administrative work.
- Collaborate on technical materials, scientific communication and activities connecting researchers, producers and companies.
- Support field operations and technical data collection when required.
BraIN & Phy Lab — UFV Laboratory Intern 2025–2026
- Maintained and monitored insect colonies used in controlled experiments.
- Supported bioinsecticide trials following standardized laboratory protocols.
- Organized experimental records and assisted with result interpretation.
- Contributed to routine quality checks required for applied research.
03 · PROJECTS
Selected systems, data and automation projects.
The cards distinguish between implemented features, experiments and areas still under validation.
AgriSentry IoT Gateway
Experimental Rust service for receiving, validating and persisting agricultural telemetry through MQTT and HTTP.
- Asynchronous message handling
- PostgreSQL persistence with SQLx
- Automated tests and load-testing exercises
RustActix WebSQLxMQTT
View repository
AgriSentry Core
Backend service for processing telemetry and applying configurable data-quality and anomaly-detection rules.
- FastAPI and asynchronous workers
- Rule-based classification baseline
- PostgreSQL, SQLAlchemy and Pytest
PythonFastAPISQLAlchemyPytest
View repository
AgriSentry IoT Platform
Reactive interface for exploring device status, telemetry records and operational monitoring workflows.
- Vue 3 composition-based interface
- API integration and responsive layouts
- Operational dashboards and status views
Vue.jsJavaScriptTailwind CSSVite
View repository
Poultry Weight Prediction
Data-analysis prototype created to explore poultry-weight forecasting, data cleaning and model evaluation workflows.
- Current public dataset is synthetic
- Streamlit interface and XGBoost model
- Requires validation with independent real data
PythonPandasXGBoostStreamlit
View repository
Nomino
Tool developed during academic event operations to generate digital certificates from spreadsheet records.
- Spreadsheet data parsing
- Template-based certificate generation
- Reduction of repetitive administrative work
PythonPandasAutomationCSV
View repository
DevGuard Core
Experimental static scanner that explores entropy and pattern-based detection for credentials and sensitive strings in source files.
- Regex and Shannon entropy checks
- Command-line workflow
- Designed as a learning project, not a security guarantee
RustCLIRegexEntropy
View repository
04 · TECHNICAL TOOLBOX
Technologies organized by how I currently use them.
Exposure, project application and core skills are intentionally separated.
Tools I prioritize
- Python
- SQL
- FastAPI
- PostgreSQL
- Git
- Docker
Tools applied in projects
- Pandas and Pytest
- SQLAlchemy and AsyncIO
- Rust and Actix Web
- MQTT and telemetry workflows
- Vue.js and Tailwind CSS
- GitHub Actions
Areas under development
- PySpark and Delta Lake
- Medallion Architecture
- Data quality and observability
- Distributed processing fundamentals
- Database performance
- Cloud deployment practices
05 · AGRIDEV
Technology is more useful when it understands the field.
AgriDev is the idea guiding my professional direction: combining agronomic knowledge with backend development and data engineering to work on problems involving traceability, telemetry, operational records and decision support.
I do not treat agriculture as a decorative niche. It is the domain in which I learned to observe variability, document processes and understand that unreliable data can lead to unreliable decisions.
Read Professional IntroductionField context
Understand the process, constraints and users before designing the system.
Reliable data
Validate, document and trace data before turning it into indicators or predictions.
Maintainable software
Use tests, clear interfaces and technical documentation to reduce avoidable uncertainty.
LET’S WORK TOGETHER
Looking for an internship or junior opportunity.
I am interested in backend development, data analysis, data engineering and technology applied to agriculture.