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Junior Data Engineer

Staffin Israel·Petaẖ Tiqva, Израиль·enhe
В офисеПолная занятостьData Engineering

Join a growing fraud prevention team building scalable data pipelines, analytics infrastructure, and data-centric software with AWS and AI-powered development tools.

Обязанности

  • Build and maintain batch and near-real-time data pipelines and ETL processes.
  • Develop data-centric software solutions using large-scale datasets.
  • Translate business and data requirements into scalable solutions.
  • Design and maintain databases, data models, and data integration processes.
  • Own data quality, monitoring, and operational reliability.
  • Analyze data and pipelines to improve fraud prevention capabilities.
  • Collaborate with data analysts, data scientists, product managers, and software engineers.
  • Participate in code reviews, design reviews, and technical decisions.
  • Use AI-powered development tools to improve development workflows.

Требования

  • At least 1 year of professional data engineering or data development experience.
  • Bachelor’s degree in computer science, industrial engineering, information systems, or a relevant technical field.
  • Strong SQL skills and experience with Python and/or shell scripting.
  • Experience with Spark, data processing, data modeling, and entity-relationship modeling.
  • Hands-on experience building or maintaining ETL processes and data pipelines.
  • Experience with AWS cloud environments, preferably S3, EC2, EMR/Spark, Redshift, Athena, or similar services.
  • Familiarity with data warehouses, data lakes, or lakehouse environments.
  • Familiarity with logging and monitoring tools such as Splunk or Grafana.
  • Hands-on experience with AI development tools such as Claude, Cursor, or similar platforms.
  • Strong analytical, problem-solving, communication, and independent working skills.
  • High level of English and Hebrew.

Будет плюсом

  • Experience in fraud prevention, cybersecurity, or financial systems.
  • Experience with agentic workflows, AI agents, skills, or plugins.
  • Knowledge of data science or machine learning.
  • Experience with NoSQL databases such as DynamoDB or Cassandra.
  • Knowledge of Scala or Java.
  • Experience with streaming or near-real-time data processing.
  • Familiarity with graph databases.

Соответствие

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