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Data Engineer

Vega·Israel·
Not specifiedNot specifiedData EngineeringCybersecurity

Build and operate the data foundations that enable production AI models and agents for a cybersecurity platform. Partner with AI engineers and researchers to deliver reliable, scalable data infrastructure.

Responsibilities

  • Design, build, and operate scalable batch and streaming data pipelines for production AI systems
  • Own ingestion, storage, transformation, serving, monitoring, and continuous improvement across the data lifecycle
  • Build data layers that make raw data semantically accessible to AI models and agents
  • Implement monitoring, alerting, and validation checks to maintain data quality and operational reliability
  • Work with data lakes, warehouses, relational, graph, and vector databases for diverse AI workloads
  • Partner with AI engineers and researchers to translate model requirements into production-grade infrastructure
  • Define and evolve the data strategy for AI applications

Requirements

  • 4+ years of professional experience in data engineering or ML infrastructure
  • Experience designing and building batch and streaming pipelines for large-scale production systems
  • Hands-on experience with data lakes, data warehouses, relational databases, and graph databases
  • Ability to build reliable, observable, and scalable infrastructure with monitoring, alerting, and data quality checks
  • Ownership of the full data lifecycle, including ingestion, modeling, serving, monitoring, and continuous improvement
  • Experience with technologies such as DuckDB, dbt, Temporal, Trino, Spark, PostgreSQL, PGVector, Neo4j, Datadog, Python, Go, Docker, and Kubernetes
  • Experience using ML models and frameworks in data pipelines, including embeddings, vector databases, or semantic search

Nice to have

  • Experience building ML/AI data infrastructure, including feature extraction and inference-time data access
  • Experience with high-volume or complex data such as logs, events, telemetry, or security data
  • Familiarity with AWS and cloud-native data tools
  • Experience translating ML and research requirements into scalable data solutions

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Data Engineer for AI Infrastructure and Data Pipelines | CVZilla