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Taboola

Content discovery and native advertising platform

Staff Engineer - Data Platform

Data EngineeringConfirmed live in the last 24 hours
Full-timeTel Aviv-Yafo, IsraelNo salary listed

About the Job

Requirements

  • At least 10 years of hands-on software engineering experience, with deep expertise in Java or an equivalent JVM/object-oriented language.
  • Deep hands-on expertise in Apache Spark, including internals, Spark SQL, the Catalyst optimizer, and performance and cost tuning at scale.
  • Production experience with Apache Iceberg or another open table format such as Delta Lake or Hudi, including table design, partitioning, compaction, and metadata/catalog management.
  • Deep expertise in Apache Kafka, including internals, partitioning and delivery semantics, and operating high-throughput pipelines in production.
  • Hands-on experience with StarRocks or a similar MPP/real-time analytics engine such as Druid, ClickHouse, or Trino.
  • Ability to introduce agent-based engineering workflows, measure their impact, and help the group adopt them.
  • Track record of designing, building, and owning large-scale distributed data systems end to end, from architecture to production reliability.
  • Experience mentoring engineers and growing technical leaders through design reviews, code reviews, pairing, and knowledge sharing.
  • Ability to influence without authority and drive alignment across teams, managers, and stakeholders.
  • High proficiency with Linux and Kubernetes in production.
  • Bachelor of Science in Computer Science or equivalent experience.

Responsibilities

  • Shape the Data Platform group's technical direction, including architecture, long-term roadmap, and technology choices.
  • Mentor and grow engineers across the group by leading design reviews, pairing on difficult problems, reviewing code, and helping engineers develop into technical leaders.
  • Set group-wide standards for design, code quality, testing, observability, and operational excellence.
  • Own major technical problems across Spark performance and cost, Iceberg table management, high-throughput Kafka ingestion, and low-latency analytics on StarRocks.
  • Evolve the Spark SQL platform and shared framework code used across R&D, deciding what to build, refactor, or retire.
  • Drive the lakehouse's evolution using Iceberg as its backbone, from ingestion through storage, compaction, and serving.
  • Serve as the go-to expert for the production health of the main data pipeline and lead deep dives and postmortems on difficult incidents.
  • Partner with team leaders, group managers, and principal engineers to shape the platform across R&D and balance stakeholder needs.
  • Write production code, build prototypes, and validate new technology before adoption.
  • Represent the group in architecture forums, hiring, open-source communities, and conference talks.

Desired Qualifications

  • Contributions to open-source data projects such as Spark, Iceberg, Kafka, or StarRocks.
  • Conference talks, blog posts, or other public technical writing.
  • Experience running Spark on GPU using RAPIDS or other query acceleration techniques.
  • Experience with stream processing, including Spark Structured Streaming, Kafka Streams, or Flink.
  • Experience with dbt and/or Airflow.
  • Knowledge of Ansible, Puppet, or similar configuration systems.
  • Track record of using AI agents to accelerate engineering work.
  • Familiarity with how machine-learning training pipelines consume data, to partner effectively with algorithm teams.

About the Company

Taboola

Content discovery and native advertising platform

Taboola helps publishers monetize content and advertisers reach audiences through a content discovery and native advertising platform. It integrates into publisher sites and shows personalized articles or videos as sponsored recommendations; advertisers pay per click and Taboola shares part of the revenue with publishers, plus analytics like Taboola Trends. The differentiators are its global network of publishers, native content-led placements, and revenue-sharing model, compared with traditional display ads. Its goal is to help advertisers drive traffic and engagement while enabling publishers to monetize content at scale on desktop and mobile worldwide.

Company size
1,001-5,000
Company stage
IPO
Headquarters
New York City, New York
Founded
2007

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