Python Developer with Backend and Big Data Expertise

I am a Python backend developer with a robust foundation in data-intensive applications, microservices, and secure systems development. With a background in physics and advanced training in Big Data and Data Science, I bring a unique mix of analytical thinking, problem-solving ability, and engineering precision to backend and data engineering roles.
My professional journey began in the biotech field, where I contributed to DNA sequence analysis tools using Django and scientific Python libraries. This early experience gave me a deep respect for data integrity, API integrations, and user security. I’ve since expanded my expertise across multiple industries—including health tech, finance, and aerospace—delivering scalable backend systems that serve critical business functions.
At BABEL Systems in Spain, I developed and maintained features for a health-tech platform, focusing on Django-based backend development, MongoDB integration, and API performance optimization. Ensuring secure handling of patient data was a top priority, and I implemented best practices for data encryption, authentication, and error monitoring.
Later, at Scalian, I worked as a Big Data Engineer supporting the banking sector. Here, I was responsible for designing and maintaining data pipelines using PySpark, Pandas, and ElasticSearch. This role sharpened my skills in handling large-scale data systems and delivering reliable pipelines with high uptime requirements, especially crucial when working with sensitive financial data.
Currently, I’m part of a multinational team at ALTEN Germany, contributing to Airbus projects. I develop internal tools and RESTful services using FastAPI, PostgreSQL, and React. This full-stack role has deepened my ability to manage data flows from backend to frontend, ensuring seamless user experiences and high-performance services.
Throughout my career, I’ve prioritized clean code, maintainable architecture, and automation. My strong command of Python, combined with tools like Pandas, Scikit-learn, NumPy, and Git, enables me to rapidly prototype, optimize, and deploy production-ready features. I’m also comfortable working in multilingual and multicultural teams—fluent in Spanish, Russian, English, and German—and have collaborated across time zones and domains with ease.
What sets me apart is my commitment to continuous learning and cross-disciplinary thinking. My academic training in physics sharpened my mathematical modeling and programming skills, while my Master’s degree in Big Data provided hands-on experience with modern data ecosystems including Hadoop, SQL/NoSQL databases, and AI frameworks like TensorFlow and Keras.
Whether building microservices, handling data pipelines, or securing endpoints, I bring reliability, curiosity, and a drive to deliver solutions that work not just today—but scale for tomorrow. I’m excited to bring this mindset and technical depth to new challenges and teams.