Summary
Ektor Makridis is a Staff Data Engineer based in London with 11 years of experience building high-throughput data platforms and backend services for analytics and reporting. He has a strong mathematical background and a pragmatic engineering style, having architected Databricks Lakehouse ETL pipelines and Kafka Streams applications that process millions of transactions daily. His work spans cost-conscious infrastructure improvements—such as query monitoring for Snowflake optimization and automated EMR cluster scaling that cut costs—and hands-on cluster ops with HDFS, Spark and YARN. Ektor pairs backend API and ETL design (Django REST, REST endpoints for visualization) with observability and CI/CD automation using Terraform, ECS, CircleCI and Grafana/Prometheus/Loki. He’s comfortable translating complex data requirements into production-ready, scalable systems and often focuses on measurable operational gains rather than purely theoretical optimizations.
11 years of coding experience
9 years of employment as a software developer
Computer Science BSc Hons, Computer Science BSc Hons at The University of Manchester