Ares Argilés García

I am a Senior Data Engineer specialized in building cloud-native data platforms on Azure and Databricks.

I design and develop scalable data pipelines using PySpark, Airflow, and dbt, with a strong focus on performance, reliability, and data quality. My main expertise lies in modern Lakehouse architectures and end-to-end data platform development.

Throughout my experience in tech and pharma environments, I have worked on building robust ingestion systems (APIs, streaming and batch), data modeling layers, and analytics-ready datasets for BI and machine learning use cases.

I am highly focused on engineering best practices such as CI/CD with GitHub Actions, automated testing, version control, and infrastructure-as-code principles to ensure scalable and maintainable systems.

In addition, I have experience with Microsoft Fabric, AWS (Cloud Practitioner), Google Data Engineer certification, and applied Generative AI in data workflows.

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