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Data Engineer - Web Attribution

AppsFlyer - Herzliya

Posted Apr 28, 2026

Benefits

Parental leave
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Non-birth-parent leave
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Family-building benefits
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  • Adoption assistance: Not verified
  • Surrogacy assistance: Not verified
Mental health support
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Relocation assistance
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Market context

U.S. role benchmark (BLS OEWS)
$111,944 U.S. median for this role
Projected growth (BLS Employment Projections)
+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function
Data From the posting source checked Jun 20, 2026
Seniority
Mid From the posting source checked Jun 20, 2026

Schedule

Shift type
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Weekend work
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Application

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Assessment
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Deadline
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Where they hire

State eligibility is not yet verified.

About this role

Data Engineer - Web Attribution Herzliya AppsFlyer processes 150+ billion events across its platform, and our Web Attribution team is at the center of extending that power beyond mobile. We're building the data infrastructure that tracks, attributes, and serves web user journeys - from first click to conversion - at massive scale across thousands of apps and billions of sessions. We're looking for a Data Engineer who wants to own the full pipeline: from raw event ingestion through distributed processing and into the serving layer that powers our clients' dashboards and APIs. This isn't internal tooling - you'll be building the actual product surface that advertisers and marketers rely on to understand what's working on the web. As AI reshapes how data is processed, queried, and served, you'll also have the opportunity to integrate AI and LLM-based capabilities into our data workflows - from intelligent data validation and anomaly detection to AI-powered analytics interfaces that make our platform smarter for clients. What you'll do - Build & Own End-to-End Pipelines: Design, build, and optimize data pipelines that process billions of web events (sessions, in-app events, conversions) with strict freshness and accuracy SLAs. You'll work across the entire attribution data stack - from ingestion and distributed processing through to the serving layer. - Ensure Data Integrity: Own the correctness of complex attribution logic - deduplication, organic vs. non-organic classification, primary attribution resolution, and cross-platform user stitching across massive, partitioned datasets. - Performance Engineering: Optimize scalable distributed processes to meet strict client

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