Daniel Turatti - Software Developer

Overview

A pragmatic Python developer (mid-level) focused on building an interactive mission simulator and module-management logic for a Mars landing scenario. The strongest proven skill is constructing domain-specific simulation and resource-management logic as shown in Turatz/fiap-fase-2/modulos/modulos.py (pousar) and Turatz/fiap-fase-2/nave.py (simular_missao and authorization). There is little evidence of formal control-theory implementations, ROS/middleware use, automated testing, or secure production practices in the public code.

Phone

Timeline

Faculdade de Administração e Informática Paulista (FIAP)

Bachelor's Degree · Computer Science

2026–2030 São Paulo, São Paulo

Projects

Financial System Expense & Income Control

Expense and income control system with recurring categories and a simple dashboard concept. Candidate built the application using Python with Django and SQLite for data storage, and used Pandas for supporting data handling. The project focuses on tracking and organizing personal finances.

Currency Converter API

API that retrieves real-time exchange rates and converts amounts between currencies. Candidate implemented the service in Python with FastAPI and integrated external rate data via HTTP requests. Output is structured for easy consumption by clients using JSON.

FinTrack

Personal finance tracker to record and organize expenses with persistence in a database. Candidate built a command-line version and plans to extend it with a FastAPI-based web version. Implemented core features using Python and SQLite, and used FastAPI and web frontend technologies in development.

Technical skills

Python

SQL

Java

Python

Django

DevOps

AWS

GitHub

Git

Rest API

AI/ML

Pandas

Jupyter Notebook

Robotics

Simulation

Autonomy

Databases

SQLite

Robotics Engineer Code level: Middle Confidence: Medium Generalist

A pragmatic Python developer (mid-level) focused on building an interactive mission simulator and module-management logic for a Mars landing scenario. The strongest proven skill is constructing domain-specific simulation and resource-management logic as shown in Turatz/fiap-fase-2/modulos/modulos.py (pousar) and Turatz/fiap-fase-2/nave.py (simular_missao and authorization). There is little evidence of formal control-theory implementations, ROS/middleware use, automated testing, or secure production practices in the public code.

Motion Control & Kinematics

2/10

Controlling robot movement

Basic mission-sequence simulation with staged altitude steps and fuel-consumption checks; not full kinematics or dynamics modeling and no singularity handling or Jacobians.

Evidence

Turatz/fiap-fase-2/modulos/modulos.py: class Modulo.pousar (descent stages, velocity updates, fuel corrections) Turatz/fiap-fase-2/nave.py: UnidadePouso.coletar (operational landing attributes used by the landing sequence)

Perception & Sensor Fusion

1/10

Understanding sensor data

Minimal sensing logic limited to boolean flags and a probabilistic obstacle detector; no sensor fusion, timestamp sync, or calibration artifacts.

Evidence

Turatz/fiap-fase-2/modulos/modulos.py: def detectar_objeto (random-based detection) Turatz/fiap-fase-2/nave.py: UnidadePouso.sensores_ok usage in _avaliar_autorizacao

ROS & Middleware

Robot software framework skills

Not evidenced in public code

Control Algorithms

2/10

Algorithms that steer robots

Simple control/decision logic and resource-aware checks (authorization decisions, fuel checks, landing-step sequencing) but no formal control algorithms (PID/MPC/LQR) or tuning records.

Evidence

Turatz/fiap-fase-2/nave.py: def _classificar_condicoes and def _avaliar_autorizacao (authorization decision logic) Turatz/fiap-fase-2/modulos/modulos.py: pousar (staged landing logic with fuel consumption checks and corrections)

Real-time Systems

Precise real-time control

Not evidenced in public code

Simulation & HIL Testing

2/10

Testing robots in simulation

Contains a bespoke command-line mission simulator and demo data loader but no CI HIL tests, no headless sim frameworks, and no documented sim-to-real validation.

Evidence

Turatz/fiap-fase-2/nave.py: def simular_missao (CLI-driven mission simulation) Turatz/fiap-fase-2/menus/menu_principal.py: def carregar_exemplo (demo data loader for simulation)

Expertise

Simulation & Digital Twins· Middle

Industries

Space & Aerospace· Middle

Technologies

Autonomy

Simulation

Recommendations

Develop CLI and simulation features, mission sequencing, and domain-model logic for prototyping spacecraft or robotic system behaviors.
Implement higher-fidelity simulation components and interfaces that enable integration with standard sim frameworks (Gazebo, PyBullet, or custom headless runners) and automated tests.
Hardening tasks such as adding unit/behavior tests, input validation suites, and secure credential handling (do not store plaintext passwords).
Design and implement lightweight decision engines or state machines that can later be migrated into ROS/robotics middleware if required.

Repositories

The developer's experience in this domain has been verified based on AI analysis of the following repositories:

fiap-fase-2 Sistema_Cadastro-Login Sistema-de-Login

Backend Developer Code level: Junior Confidence: Medium Generalist

Backend Developer (junior level) specializing in Django-based web applications and user authentication. The strongest proven skill is implementing standard Django authentication flows and protected views as shown in meu_projeto/accounts/views.py. There is little to no evidence of REST API design, production-grade migrations history, performance tuning, resilience patterns, or automated tests in public code.

API Design

1/10

How well APIs are designed

Minimal API design artifacts; only Django view/url handlers for web auth flows exist and no versioning, idempotency, pagination, or error contract design for an API surface.

Evidence

Turatz/Sistema_Cadastro-Login/meu_projeto/accounts/views.py: register/login_view handling POST/GET without structured API contract Turatz/Sistema_Cadastro-Login/meu_projeto/meu_projeto/urls.py: app-level URL routing (accounts/ and core/) with no API versioning

Data Layer & Database

2/10

Working with databases

Basic data layer usage is present via a custom user model migration; there is a single initial migration and no evident schema evolution, advanced transactions, or hand-tuned queries.

Evidence

Turatz/Sistema_Cadastro-Login/meu_projeto/accounts/migrations/0001_initial.py: CustomUser model with fields including unique email and email_verified Turatz/Sistema_Cadastro-Login/meu_projeto/accounts/views.py: uses Django ORM-backed authentication flows

Scalability & Performance

1/10

Handling load and speed

No demonstrated scalability or performance engineering; no caching, queueing, connection-pooling configuration, or load-test artifacts.

Evidence

Turatz/Sistema_Cadastro-Login/meu_projeto/accounts/views.py: synchronous request handlers without caching or rate-limiting

System Architecture

2/10

Overall system structure

Simple, conventional Django app decomposition into apps (accounts, core) is present but there is no evidence of deliberate service decomposition, inter-service contracts, or resilience boundaries.

Evidence

Turatz/Sistema_Cadastro-Login/meu_projeto/meu_projeto/urls.py: includes accounts and core apps via include() Turatz/Sistema_Cadastro-Login/meu_projeto/manage.py: standard Django project entrypoint showing conventional single-project layout

Security & Auth

3/10

Protecting data and access

Concrete, correct use of Django authentication primitives and login_required decorator shows practical auth knowledge, but there is no evidence of token lifecycle, refresh/revocation, or hardened input validation beyond Django defaults.

Evidence

Turatz/Sistema_Cadastro-Login/meu_projeto/accounts/views.py: use of authenticate(), login(), logout(), and @login_required for dashboard Turatz/Sistema_Cadastro-Login/meu_projeto/accounts/migrations/0001_initial.py: unique email constraint on CustomUser

Reliability & Observability

1/10

Stability and monitoring

Very limited reliability and observability artifacts; no structured logging, metrics, timeouts, retry/backoff, or graceful shutdown patterns are present in the human-authored code.

Evidence

Turatz/Sistema_Cadastro-Login/meu_projeto/accounts/views.py: standard view flow with messages but no logging/metrics or retry logic

Expertise

Python· Junior

Technologies

Python· since 2025 · Middle · 3 projects

Rest API· since 2026

Django· since 2025 · 3 projects

Recommendations

Develop small to medium Django web applications that require user registration, authentication, and basic dashboards.
Implement REST APIs or GraphQL endpoints on top of existing Django apps to gain API design experience including versioning and error contracts.
Add automated tests (unit and integration) and a migration history for schema evolution to demonstrate data layer discipline.
Introduce basic observability and resilience patterns such as structured logging, timeouts, and simple rate limiting or caching for common endpoints.

Repositories

The developer's experience in this domain has been verified based on AI analysis of the following repositories:

financeiro Turatz Sistema_Cadastro-Login

AI/ML Engineer Confidence: Low Generalist

A beginner-level developer focused on simple Python scripting and Jupyter Notebook-based exercises. The strongest proven skill is building a simple interactive pre-departure check implemented in NotebookPython.ipynb. There is no evidence of production engineering, tests, CI/CD, model training, or deployment infrastructure in the public artifacts.

Model Architecture & Training

How well models are designed and trained

Not evidenced in public code

Data Pipeline & Feature Engineering

How data is prepared for models

Not evidenced in public code

Experimentation & Evaluation

How results are measured and tested

Not evidenced in public code

MLOps & Deployment

How models are shipped to production

Not evidenced in public code

Computational Efficiency

How efficiently computing resources are used

Not evidenced in public code

Research Depth & Innovation

Depth of research and new ideas

Not evidenced in public code

Industries

Space & Aerospace· Junior

Technologies

Jupyter Notebook

Pandas

Git· since 2026

SQLite· since 2026

AWS

GitHub· since 2026

Recommendations

Develop small CLI or script-based utilities and add unit tests to demonstrate engineering rigor and error handling.
Convert the notebook logic into modular Python scripts or a small package with functions and a clear entrypoint for easier reuse and testing.
Add CI configuration, basic linting, and a test matrix to show familiarity with development tooling and reliability practices.
If interested in ML or MLOps, create a minimal experiment pipeline and tracking (W&B or MLflow) with a reproducible dataset split to demonstrate model engineering skills.

Repositories

The developer's experience in this domain has been verified based on AI analysis of the following repositories:

fiap-fase-1 Turatz

Job preferences

Work permits: Brazil
Employment type: Full-Time