We're looking for someone with a strong foundation in data Engineering within a Big Data & Cloud environment, who can quickly learn and adapt to new technologies and help expand our data Engineering capabilities while working closely with analysts, data scientists, and software developers in the Fraud Prevention domain.
What You'll Do:
Gather data requirements from Product and Analytics teams and translate them into scalable data solutions.
Build and maintain data pipelines, ETL processes, and data -centric applications using Big Data technologies.
Own data assets end-to-end, including data quality, monitoring, and operational support.
Collaborate closely with stakeholders, analysts, data scientists, and developers.
Influence data architecture and best practices across the team.
Requirements: What We're Looking For:
Degree in Information Systems, Industrial Engineering, Computer Science, or relevant experience (e.g., military tech units).
Strong business understanding and ability to translate complex product flows into data solutions.
Experience working directly with internal customers.
Expert-level SQL in large-scale environments (Spark, Databricks, Presto, Athena, Trino, Redshift).
Hands-on experience with ETL /pipeline development, monitoring, and orchestration.
Cloud experience, preferably AWS (EMR/Spark, S3, EC2).
Familiarity with logging & monitoring tools (Splunk, Grafana) and data modeling.
Python & Shell scripting in Linux environments.
Fluent Hebrew and English.
Experience with AI-powered development tools and Agentic environments (Claude, Cursor, etc.).
This position is open to all candidates.
