Summary
Ferran Ferri is a Big Data and Scala-focused data engineer with 11 years designing and operating real-time and batch data platforms across international companies from Barcelona. He has led cross-functional squads and driven platform improvements—introducing idempotent ETL patterns, Airflow orchestration, and production Scala/Akka/Kafka systems—while shifting heavy Spark workloads toward lightweight Python ETLs and cloud-native tooling. Comfortable oscillating between data-engineering and platform roles, he brings hands-on experience with ZIO, Kafka Streams, Prometheus/Grafana, Kubernetes and AWS streaming services. His background combines deep distributed-systems training (MSc from Chalmers) with an honors MSc in Big Data and an applied NLP/Deep Learning thesis, which helps him bridge low-level systems reliability with ML-driven product features. Notably, he has repeatedly owned architecture changes that improved operational reliability and observability in high-throughput delivery and marketing platforms.
11 years of coding experience
9 years of employment as a software developer
Master’s Degree, MSc in Big Data, Thesis based in NLP - Deep Learning colaboration with Accenture: Matricula Honor, Master’s Degree, MSc in Big Data, Thesis based in NLP - Deep Learning colaboration with Accenture: Matricula Honor at Universitat Ramon Llull
Master's Degree, MSc Networks and Distributed Systems, (SWEDEN) 120 ECTS, Master's Degree, MSc Networks and Distributed Systems, (SWEDEN) 120 ECTS at Chalmers University of Technology
Universitat Politècnica de València
Spanish, Catalan, English, Swedish