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Data Engineer

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Onsite

Data Engineer

Hire-Match

Data Engineer

Skills

Google Cloud PlatformSQL QueriesPythonKafkaSnowflakeData AnalysisMachine LearningAIScalaAWSdbtApache AirflowTerraformAzure

2 months ago

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Important information


Contract type:

Permanent

Location:

Ramat Gan, Israel

Work mode:

Onsite

Published on:

24 August 2026

What they need


HireMatch builds an AI-powered hiring platform that turns resumes, assessments, interviews, and candidate data into structured insights to help teams make faster, fairer, and more confident hiring decisions. We go beyond keyword matching with context-aware evaluation, predictive fit signals, and real-time dashboards that surface top candidates instantly. Our mission is to undo the hiring black box and bring transparency, merit, and measurable impact to recruiting — all powered by scalable AI and analytics.

Position Description

As a Data Engineer, you will design and maintain the data infrastructure that powers reporting, analytics, and product features across the company. You will work closely with data and engineering teams to ensure data is reliable, accessible, and well-modeled.

Responsibilities

  • Design, build, and maintain ETL/ELT pipelines that move and transform data across company systems
  • Own data pipeline reliability, including monitoring, alerting, and incident response
  • Collaborate with data analysts, scientists, and engineering teams to meet their data needs
  • Optimize data storage and query performance in the company's cloud data warehouse
  • Maintain data quality and documentation standards across pipelines

Must Have

  • 2-5 years of hands-on experience with SQL and Python (or Scala) for data pipeline development
  • Experience designing and orchestrating ETL/ELT pipelines (Airflow, dbt, or equivalent)
  • Experience with a cloud data warehouse platform (Snowflake, BigQuery, or Redshift)
  • Experience with a major cloud platform for data infrastructure (AWS, GCP, or Azure)
  • Working knowledge of data modeling fundamentals

Nice to Have

  • Experience with distributed data processing (Spark) and/or streaming pipelines (Kafka)
  • Data quality / governance framework experience
  • Experience building pipelines that feed ML/AI systems
  • Infrastructure-as-code (Terraform) for data infrastructure

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