Eyal Levy is a Data Engineers Team Lead based in Israel with over a decade of hands-on experience building and optimizing large-scale data platforms. He has led teams through migrations from legacy ETL to modern data lakes, designing Spark, Kafka, Databricks and Airflow pipelines that process tens of billions of records and serve ~500 active users. Eyal combines deep cost-optimization instincts—achieving six-figure savings via infrastructure and storage improvements—with a developer-first mindset that enabled self-service analytics and DBT-driven feature engineering. He has repeatedly grown junior engineers into senior contributors while remaining a pragmatic, hands-on coder and troubleshooter across Spark, Kubernetes, and distributed systems. A detail that often goes unnoticed: his background in enterprise Java and distributed platform work informs his ability to bridge product, data science and ops needs in complex regulated domains like financial fraud detection.
11 years of coding experience
12 years of employment as a software developer
Bachelor of Science - BS Computer Science & Mathematic, Bachelor of Science - BS Computer Science & Mathematic at Bar-Ilan University
POC for all the stack of big data (kafka, spark, cassandra, hdfs, docker, springboot)
Contributions:1 review, 27 commits, 7 PRs in 4 years 10 months
kuducassandraspringbootdockerbig-data
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