Home - Curriculum Vitae

Darlan Noetzold, MSc

Developer & Researcher

PROFILE

Ph.D Student at University of Salamanca, Spain. Master in Applied Computing from UNISINOS and Computer Scientist graduated from IFSul, currently working as a Mid-level Programmer at CWI Software. I also hold an MBA in Big Data and Competitive Intelligence, as well as a postgraduate degree in Software Engineering and Cloud Computing. I have always been passionate about Mathematics and creating. I feel that programming and the technology field in general can associate both worlds. This convergence of logic and creativity has always inspired me to think further and execute my projects. Combined with a study routine and dedication to what I love, it has brought me to where I am today. Without a doubt, this area is my source of dopamine at the end of the day.

TECHNICAL SKILLS

Backend & APIs

JAVA

JAVA EE

Spring Framework

Quarkus

Python (FastAPI, Django, Flask)

Microservices (API’s, Mocks)

Node.js/Nest.js

Message Brokers (Kafka, RabbitMq, ActiveMq)

Caching (Redis)

E-commerce

Frontend & Mobile

React

HTML5 & CSS3

JavaScript/TypeScript

Android (Native, Flutter)

Cloud & Infrastructure

DevOps (Docker, Vagrant, K8s)

Clouds (AWS, OCI, Google Cloud)

OS (Linux, Windows)

Raspberry Pi

Network Infrastructure

Quality, Architecture & Security

Java Profiling (JMR, JMeter, VisualVM, JProfile)

Tests (Junit, Mockito, JMeter)

CyberSecurity (Data Privacy, Cryptography)

Observability (Graylog, Dynatrace, Grafana)

Project/Design Patterns

Rust

FOCUS OF STUDY

Java

Object-oriented Java, Spring APIs and microservices, testing, containers, CI/CD, messaging, caching and distributed systems.

Machine Learning

Applied machine learning with Python: data preparation, statistical methods, supervised learning, neural networks, optimization and evaluation.

Python

Python APIs and data science with Flask, Django, NumPy, Pandas, Matplotlib, scikit-learn, PyTorch and automation.

Adaptive Security Engineering

Security mechanisms that adapt cryptographic choices to context, balancing protection, performance and operational requirements. Informed by PRISEC III and Q-OPSEC adaptive middleware research.

Self-Adaptive Smart Systems

Intelligent environments observe context, anticipate changes and adjust behavior to sustain performance and service quality. Inspired by Oraculum and self-adaptive systems research.