Looking for a job

Francisco Javier Urías Ortiz

@franciscojavieruraso

Message

Data Engineer at SINECTA.IA who built an agricultural assessment app for recurring business use.

Mexico

Message

At SINECTA.IA, I built reusable Python ETL pipelines and developed a Streamlit agricultural assessment application that combined satellite-derived NDVI, crop phenological stage, and historical field information. The application supported recurring business use, including weekly and on-demand assessments.

I also built a document assistant with LangChain and OpenAI APIs that retrieves source passages for LLM-generated answers. My M.Sc. research at CICESE applied machine learning and statistical analysis to multi-year urban land-cover change data.

Experience

Work history, roles, and key accomplishments

Current

Data Engineer

Current

SINECTA.IA

Mar 2025 - Present (1 year 7 months)

Built reusable Python ETL pipelines integrating REST APIs, PostgreSQL, CSV files, and external sources for analytics and machine learning. Developed a Streamlit agricultural assessment application and a RAG document assistant.

Python SQL ETL REST APIs PostgreSQL Snowflake Databricks PySpark Streamlit Lang Chain OpenAI API Docker Git A B Testing Validation Unit Testing

Validation Engineer

LANIX

Feb 2022 - Aug 2023 (1 year 6 months)

Developed Python tools for quality assurance, operational monitoring, and incident analysis. Applied statistical analysis to production performance.

Python Quality Assurance Statistical Analysis Monitoring

Process & Maintenance Engineer

LATECOERE

Aug 2021 - Feb 2022 (6 months)

Analyzed manufacturing data, automated tasks with Python and Excel, and performed root cause analysis to identify operational improvements.

Python Excel Data Analysis Root Cause Analysis Automation

Education

Degrees, certifications, and relevant coursework

CICESE

M.Sc., Electronics & Telecommunications

2023 - 2026

M.Sc. in Electronics & Telecommunications with a thesis on multi-year urban land-cover change detection, combining machine learning, remote sensing, and statistical analysis.