I am a data engineer focused on building reliable, scalable, and maintainable data pipelines. With a strong foundation in Python, SQL, and PostgreSQL, I design and implement workflows that ingest, transform, and load data efficiently using modern orchestration tools like Apache Airflow and containerized environments with Docker.
I have hands-on experience developing ETL pipelines, integrating external APIs, and structuring staging layers for analytical use. I follow best practices in data modeling, pipeline design, and system reliability to ensure data quality and consistency across workflows.
Currently, I am transitioning toward a modern ELT approach—emphasizing SQL-based transformations and scalable data architectures—and expanding into cloud-based solutions. I’m seeking opportunities to work on real-world data platforms, contribute to production-grade pipelines, and continue growing as a data engineer.
