I work as a Backend Engineer building APIs and data pipelines for a financial analytics platform.

• Built Django REST APIs for NAV calculations, portfolio performance and reporting.
• Deployed services on AWS using EC2, Docker, RDS and Route 53.
• Created CI/CD pipelines with GitHub Actions, including tests, Docker image generation and auto-deploy.
• Orchestrated Celery pipelines and processed data with Pandas, NumPy and Polars.
• Improved performance and generated Excel and PDF reports with WeasyPrint.

I designed and built a full data reduction pipeline to process hundreds of GB of astronomical images obtained by the telescope.

• Implemented core algorithms in C/C++ and Python for bias/dark subtraction, flat-fielding and astrometric calibration.
• Used NumPy, Pandas and Astropy for scientific processing and pipeline performance improvements.
• Worked with Linux servers and Docker to package and deploy the pipeline containers.
• Collaborated with the astrophysics team to improve data quality and results.

Research project: "Smart ports and electrification of internal traffic in the Canary Islands ports".

• Developed a LoRaWAN-based IoT infrastructure to monitor traffic.
• Processed sensor data with Raspberry Pi, Python and C++, and built real-time pipelines with MQTT.
• Managed storage and monitoring with InfluxDB, MySQL and Grafana.
• Built web interfaces with React and Next.js, and deployed services with Docker on Linux virtual machines.

I worked on processing and visualising maritime telemetry data from multiple vessels.

• Processed and cleaned data with Python, Pandas, NumPy and Folium.
• Built a FastAPI backend and a React frontend for geospatial visualisation and metrics.
• Integrated Leaflet and Bootstrap for interactive maps and responsive design.
• Visualised more than 10 vessels and hundreds of thousands of positioning data points.

Through a scholarship granted by the General Foundation of the University of La Laguna.

I developed a full-stack application for processing and visualising vehicle traffic data.

• Built the backend with Django to process, transform and store large volumes of data.
• Built a responsive frontend with React, JavaScript and Bootstrap for analytics dashboards.
• The platform was used internally to support traffic analysis and urban planning.