Julio

Data Engineer with a master's degree in data analytics and 10 years of experience building engineering and analytics solutions to transform complex information into high-impact decisions. I specialize in advanced SQL, database modeling and optimization, ETL/ELT pipeline design, and the development of predictive models and LLM agents. I combine applied statistics, backend, and cloud technologies to create scalable, reliable, and results-oriented solutions.

Data Engineer - Freelancer

(2026-01)

• Provided data engineering services to multiple clients as a freelancer, designing and implementing ETL pipelines from on-premise databases and flat files into Cloud as Databricks and BigQuery on GCP.

Data Engineer - Kairos DS

(2023-01 - 2026-01)

• Led the development of ETL processes using Apache Beam and Google Dataflow for the batch migration of large volumes of data from on-premise databases to Cloud SQL, reducing transfer times from days to hours and standardizing this technology as an innovation model for other areas of the organization.
• Applied reengineering and optimization to multiple critical legacy systems to improve operational efficiency, achieving superior performance in stability and response speed.

FullStack Developer - Sail Technologies

(2020-01 - 2023-01)

• Developed fullstack solutions for government, medical, and technology platforms to optimize administrative processes and improve interoperability.

FullStack Developer / Data Engineer - Hospital Civil de Culiacán

(2015-01 - 2023-01)

• Participated in the development of reports and dashboards, optimizing strategic decision-making and achieving measurable improvements in KPIs.
• Developed a chatbot for automated delivery of clinical results via WhatsApp, optimizing logistical efficiency and reducing in-person crowding during the COVID-19 contingency.
• Implemented an LLM agent with RAG architecture and a chatbot interface, enabling automated extraction of clinical records and improving the speed of medical analysis for more precise and detailed diagnoses.
• Participated in research by developing and tuning predictive models for anesthetic and cardiac risk using hospital data, which were implemented in clinical practice to support medical decision-making, accurately adapting parameters to the local population.
• Developed streaming data pipelines to maintain data parity between the legacy system and the core system, achieving low-latency synchronization.
• Performed statistical analysis and report generation through data extraction, optimizing strategic decision-making and achieving measurable improvements in KPIs.
• Played a central role in the design and development of an integrated management system covering both medical and administrative areas, significantly improving healthcare delivery capacity and overall productivity.

Bachelor's Degree - Computer Systems Engineering - Instituto Tecnológico de Mazatlán (2010-01 - 2015-01)

Certificate - Machine Learning - Stanford Online (2018-01)

Certificate - Deep Learning - DeepLearning.AI (2019-01)

Master's Degree - Big Data Analysis and Visualization - Universidad Internacional de la Rioja (2019-01 - 2021-01)