Ares Argilés García

I'm a Senior Data Engineer specialized in building cloud-native data platforms on Azure, Databricks, and Microsoft Fabric, with a focus on Lakehouse architectures and scalable, maintainable pipelines.

In my current project for a German marketplace, I was part of the team that migrated a SQL- and Airflow-based architecture to a modular dbt-based model, designing around 10 models (staging, intermediate, marts) integrated into Airflow orchestration. This migration significantly improved code maintainability and pipeline execution times.

In the pharmaceutical sector, I worked on cleaning and enriching highly unstructured third-party data, transforming it into curated, analytics- and ML-ready datasets, applying Delta Lake best practices to improve reliability and governance.

My core stack includes PySpark, Airflow, dbt, Microsoft Fabric, Delta Lake, and CI/CD tooling (GitHub Actions, Docker) to ensure production-ready, maintainable systems. I also hold certifications in AWS Cloud Practitioner and Google Data Engineer, along with experience applying generative AI to data quality workflows.

If you're looking to build or scale a modern data platform on Azure or Databricks, I can help you design and deliver a reliable, production-ready solution.