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Rafael Cervantes

@rafaelcervantes1

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Software Engineer specializing in scalable backend systems and cloud solutions.

United States

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What I'm looking for

I'm looking for a role that fosters innovation and values continuous improvement.

I'm a dedicated Software Engineer with a strong background in architecting and deploying scalable, high-performance backend systems. My expertise lies in Python, AWS, and modern web frameworks, which I leverage to deliver impactful software solutions for enterprise change management analytics and geospatial data platforms. I take pride in managing projects from ideation to production, focusing on infrastructure optimization and creating reliable, secure, and user-centric applications.

At BiasSync, I architected and deployed a scalable, client-facing RESTful API using Python/Flask and AWS services, significantly reducing manual engineering intervention. My initiatives have led to increased click-through rates and operational cost savings. I also refactored core architecture to support multi-lingual content, enhancing the user experience for a global audience. My experience at Coperniq involved engineering an automated data pipeline that drastically increased data acquisition efficiency, showcasing my ability to streamline processes and deliver results.

Experience

Work history, roles, and key accomplishments

Current

Software Engineer

Current

BiasSync

Jul 2021 - Present (4 years 2 months)

Architected and deployed a scalable, client-facing RESTful API using Python/Flask and AWS services (API Gateway, Lambda, S3, RDS), which enabled self-service roster management and significantly reduced manual engineering intervention. Refactored the email delivery system by strategically migrating templates to a unified S3 bucket and modernizing application code, leading to a 20% increase in click

Python Flask AWS API Gateway Lambda S3 RDS Terraform Google Sheets

Software Engineer

Coperniq

Nov 2020 - Present (4 years 10 months)

Engineered a comprehensive, automated data pipeline using Python and Selenium, which significantly reduced manual efforts and drastically increased data acquisition efficiency. Developed a Geographic Information System (GIS) layer using GeoPandas and Mapbox that visually displayed national boundaries and responsible authorities on the platform's map view, fueled by the automated data pipeline. Int

Python Selenium Geopandas Mapbox Google Maps GIS Data Pipelines

Education

Degrees, certifications, and relevant coursework

University of California, San Diego

Bachelors of Science, Computer Science

2017 - 2020

Activities and societies: Hispanic Scholarship Fund Scholar, Member, Society of Hispanic Professional Engineers

Studied Computer Science, gaining a strong foundation in software development and data analysis. Participated in academic and professional development programs.