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Victor Hugo Rios Torres

@victorhugoriostorres

Data Engineer at High 5 Games who built a Gemini-powered image-understanding app and improved welcome-package test retention by ~10%.

Mexico

Message

What I'm looking for

I’m looking to apply my engineering and data foundation to AI solutions in financial services.

At High 5 Games, I built an internal AI application using Streamlit and the Gemini API to understand images, generate descriptions, and return structured JSON, reducing manual content processing.

I design and operate GCP data pipelines over high-volume event and transaction data, and integrate machine-learning models into production. In welcome-package A/B tests, retention improved by about 10%, varying by the ad shown.

Previously, I reduced latency by 30% in e-commerce backend systems at Globant and built ETL pipelines at UTEL Universidad that cut manual reporting from three hours to five minutes. I’m looking to apply my engineering and data foundation to AI solutions in financial services.

Experience

Work history, roles, and key accomplishments

Current

Data Engineer

Current

High 5 Games

May 2023 - Present (3 years 5 months)

Built an internal AI application using Streamlit and Gemini API for image understanding and automated descriptions. Designed and operated ETL/ELT pipelines on GCP and optimized BigQuery workloads.

Python Streamlit Gemini API GCP Airflow BigQuery dataform Pub Sub A B Testing CI CD Docker Bitbucket Pipelines Jenkins

Python Developer

Globant

Dec 2020 - Apr 2023 (2 years 4 months)

Reduced latency by 30% in high-scale e-commerce backend systems with asynchronous processing and improved observability with AWS CloudWatch. Mentored junior developers and introduced TDD practices.

Python Cloudwatch Asynchronous Processing Test Driven Development Mentorship

Python Developer

Aptude

Nov 2019 - Nov 2020 (1 year)

Migrated monolithic systems to microservices using Django and Flask REST APIs. Automated workflows with Bash and deployed with Docker and Redshift.

Python Django Flask REST APIs BASH Docker Redshift Microservices

Python Data Analyst

UTEL Universidad

Dec 2017 - Nov 2019 (1 year 11 months)

Built ETL pipelines with Django, Pandas, and NumPy that reduced manual reporting time from 3 hours to 5 minutes. Created dashboards with Flask and Power BI and automated ingestion from AWS/SAS with CI/CD.

Python Django Pandas NumPy Flask Power BI AWS SAS CI CD Jenkins GitHub Actions

Education

Degrees, certifications, and relevant coursework

UNIR Mexico

M.Sc., Artificial Intelligence for the Financial Sector

2026 -

In progress, starting November 2026, focusing on AI applied to risk and investments, machine learning and deep learning, data ethics, privacy and governance.