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Junior Data Engineer
במקום העבודהמשרה מלאהData Engineering
Join a growing fraud prevention team building scalable data pipelines, analytics infrastructure, and data-centric software with AWS and AI-powered development tools.
תחומי אחריות
- 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.
דרישות
- 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.
יתרון
- 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.