Data Analytics | Data Engineering & Cloud & ML

Hello, I'm
Jorge Tito

I build end-to-end data systems — from real-time ingestion and processing to analytics, visualization, and intelligent decision-making. My work combines data engineering, cloud-native architectures (AWS), and applied machine learning, with a focus on scalability, robustness, and real-world impact.

• Real-time data pipelines (streaming & serverless)
• Data lakes and SQL-based analytics
• Machine learning for time-series data
• Cloud architecture with AWS & Infrastructure as Code

Core Expertise

My work focuses on building scalable data systems that combine analytics, cloud-native architectures, and applied machine learning.

Data Analytics

Exploring data, identifying patterns, and generating insights through visualization and analytical thinking.

Data Engineering

Building scalable data flows for ingestion, transformation, and processing across different systems.

Cloud Architecture

Designing cloud-native solutions focused on scalability, reliability, and efficient system design.

Machine Learning

Applying machine learning to solve real-world problems with focus on performance and robustness.

Featured Projects

Selected projects that showcase my work in data systems, cloud architecture, and applied machine learning.

EEG Event Analytics Pipeline on AWS

Cloud & Fog & Data Engineering

Pipeline fog-cloud orientado a eventos para la ingesta, persistencia, análisis y notificación de eventos EEG utilizando servicios de AWS.

Fog ComputingCloud ComputingAWS KinesisAWS LambdaAWS S3AWS DynamoDBAWS GlueAmazon AthenaAmazon SNSIAMIaCEvent-Driven ArchitectureData LakeEEG Signal Processing

EEG Seizure Detection with CNN–Transformer + Adversarial Learning

Machine Learning & Signal Processing

Automatic seizure detection in multi-channel EEG using a hybrid CNN–Transformer model with adversarial learning for cross-patient generalization.

PythonPyTorchDeep LearningCNNTransformersAdversarial LearningTime SeriesSignal ProcessingEEG