Summary
Georvic Tur is a Staff Data Engineer with 11 years of experience building scalable data platforms, ML pipelines, and distributed systems across cloud environments (GCP, AWS, Azure) from Madrid. He combines a strong research background in signal processing and ML—applied to speech and biomedical data—with hands-on expertise in data engineering tools like dbt, Airflow/Dagster/Prefect, BigQuery, Snowflake, Spark and Kubernetes. At companies from startups to enterprise, he has led production migrations, CI/CD and observability initiatives (dbt, DataHub, Monte Carlo, Elementary) and championed cost, governance and MLOps best practices. Comfortable in interdisciplinary teams, he bridges algorithmic R&D and robust engineering, often translating experimental ML into production-ready services. A polyglot developer (Python, Scala, Java, Haskell) with a taste for architecting event-driven, microservices systems, he also contributes thorough documentation and operational tooling to keep complex data ecosystems reliable.
11 years of coding experience
8 years of employment as a software developer
Bachelor of Engineering Computer Science, Bachelor of Engineering Computer Science at Universidad Simón Bolívar
English, Spanish, German, Chinese