Staff Engineer — Data Platform

Posted 15 Hours Ago
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Tel Aviv, ISR
Hybrid
Expert/Leader
AdTech • Big Data • Digital Media • Marketing Tech
Taboola empowers businesses to grow through performance advertising technology that goes beyond search and social.
The Role
Lead the technical direction of a large-scale data platform supporting reporting, billing, machine learning, experimentation, and business decisions. Design and operate distributed systems using Spark, Iceberg, Kafka, and StarRocks; improve reliability, performance, cost, and observability; mentor engineers; guide architecture and roadmaps; and remain hands-on with production code, prototypes, incident response, and cross-functional technical leadership.
Summary Generated by Built In

Realize your potential by joining the leading performance-driven advertising company!

As a Staff Engineer - Data Platform on the infrastructure department in ourTel Aviv Office, you’ll play a vital role in as a Staff Engineer – Data Platform in the Infrastructure Department in our Tel Aviv office, you’ll play a vital role in building the core data platform that powers Taboola’s reporting, billing, ML training, experimentation, revenue optimization, and business decision-making — ensuring data is reliable, fresh, scalable, and easy to use.

You’ll be a senior technical leader across the Data Platform group, owning the hardest technical challenges across Spark, Iceberg, Kafka, and StarRocks. As a hands-on individual contributor, you’ll drive technical excellence and make every engineer around you better through mentoring and technical leadership.

1.4 billion users. 950,000 requests per second. 150TB of fresh data every day. 800M metrics every minute. That's the scale Taboola's Data Platform group operates at.


To thrive in this role, you'll need:

  • 10+ years of hands-on software engineering, with deep expertise in Java or an equivalent JVM/object-oriented language
  • Deep, hands-on expertise in Apache Spark — internals, Spark SQL and 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) — table design, partitioning, compaction, and metadata/catalog management
  • Deep expertise in Apache Kafka — 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 (Druid, ClickHouse, Trino)
  • Lead by example with AI: introduce agent-based engineering workflows, measure their impact, and help the group adopt them
  • A track record of designing, building, and owning large-scale distributed data systems end to end — from architecture to production reliability
  • Proven 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
  • Highly proficient with Linux and Kubernetes in production
  • B.Sc. in Computer Science or equivalent experience

Bonus points if you have:

  • Contributions to open-source data projects (Spark, Iceberg, Kafka, StarRocks, or similar)
  • Conference talks, blog posts, or other public technical writing
  • Experience running Spark on GPU (RAPIDS) or other query acceleration techniques
  • Experience with stream processing (Spark Structured Streaming, Kafka Streams, Flink)
  • Experience with dbt and/or Airflow
  • Knowledge of Ansible, Puppet, or similar configuration systems
  • A track record of leveraging AI agents to accelerate engineering work
  • Familiarity with how ML training pipelines consume data, to partner effectively with algo teams

How you’ll make an impact:

  • Shape the technical direction of the Data Platform group — the architecture, the long-term roadmap, and the bets we make on emerging tech (Iceberg, StarRocks, GPU Spark, dbt, AI tooling)
  • Mentor and grow engineers across the group: lead design reviews, pair on hard problems, review code with care, and help strong engineers grow into technical leaders
  • Raise the engineering bar group-wide — set standards for design, code quality, testing, observability, and operational excellence
  • Own the hardest problems on our stack: Spark performance and cost across 60,000+ jobs/day, Iceberg table management at Taboola scale, high-throughput Kafka ingestion, and low-latency analytics on StarRocks
  • Evolve our Spark SQL platform and the core framework code used across R&D — making the call on what gets built, refactored, or retired
  • Drive the evolution of our lakehouse, with Iceberg as the backbone — from ingestion through storage, compaction, and serving
  • Be the go-to expert for the production health of the main Taboola data pipeline — the system behind reports, ML model training, billing, and other business-critical processes — and lead deep-dives and postmortems on the toughest incidents
  • Partner with team leaders, group managers, and fellow principal engineers to shape how the platform evolves across R&D, balancing the needs of algo, product, finance, and infrastructure stakeholders
  • Stay deeply hands-on — write production code, build prototypes, and prove out new technology before the group commits to it
  • Represent the group internally and externally — in architecture forums, hiring, open-source communities, and conference talks
  • Directly shape how billions of people discover the internet

Here are some of the things engineers in our group have done — or are doing right now
  • Pioneered deployment of Spark SQL workloads on GPU with RAPIDS
  • Delivered a real-time pipeline reports product serving all our customers on top of Druid
  • Actively migrating a proprietary ETL system to dbt-core
  • Pioneered usage of Iceberg (and gave conference talks about it) — yes, we manage it ourselves
  • Productionizing our StarRocks deployments
  • Building pipelines on top of Spark Streaming, Iceberg, and dbt
  • Extending data solutions to help algo engineers iterate fasterOur Tech Stack

Java, Spark, Kafka, Iceberg, Hadoop, Cassandra, Vertica, StarRocks, MySQL, HDFS, BigQuery, Docker, Linux, Kubernetes, Prometheus, Grafana, Airflow, dbt, Druid

Why Taboola?

If you ask Taboolars what they love about working here, they’ll tell you that they’ve been empowered to realize their full potential while growing and learning from and with smart and talented people. They’ll also share more about:

  • Adam Singolda, Taboola Founder and CEO says; “You can copy anything from another business but you can’t copy a company’s culture.”
  • Well-being: Competitive benefits and well-being programs tailored to the region, including comprehensive health benefits, a fully stocked kitchen, and location-specific perks.
  • Flexibility: We offer a hybrid work schedule with 3 days in-office with an option to come in more often if desired.
  • Work with some of the biggest names: Our publisher partners include Yahoo, Conde Nast, Fox Sports, NBCU, ESPN, CBS, and E! Online. Our advertiser clients include Wells Fargo, Honda, Pinterest, and Expedia.

Ready to realize your potential?

Taboola is an equal opportunity employer and we value diversity in all forms. We are committed to creating an inclusive environment for all employees and believe such an environment is critical for success. Employment is decided on the basis of qualifications, merit, and business need.

Learn more about #TaboolaLife on LinkedIn, Instagram, X, & the Taboola Life Blog.

About Taboola

Taboola empowers businesses to grow through performance advertising technology that goes beyond search and social and delivers measurable outcomes at scale.

Taboola works with thousands of businesses who advertise directly on Realize, Taboola’s powerful ad platform, reaching approximately 600M daily active users across some of the best publishers in the world. Publishers like NBC News, Yahoo, and OEMs such as Samsung, Xiaomi and others use Taboola’s technology to grow audience and revenue, enabling Realize to offer unique data, specialized algorithms, and unmatched scale.


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#LI-Hybrid

Skills Required

  • 10+ years of hands-on software engineering experience
  • Deep expertise in Java or an equivalent JVM/object-oriented language
  • Deep hands-on expertise in Apache Spark, including internals, Spark SQL, Catalyst optimizer, and performance and cost tuning
  • Production experience with Apache Iceberg or another open table format such as Delta Lake or Hudi
  • Deep expertise in Apache Kafka, including internals, partitioning, delivery semantics, and high-throughput production pipelines
  • Hands-on experience with StarRocks or a similar MPP/real-time analytics engine
  • Experience designing, building, and owning large-scale distributed data systems end to end
  • Experience mentoring engineers and growing technical leaders
  • Ability to influence without authority and drive alignment across teams and stakeholders
  • High proficiency with Linux and Kubernetes in production
  • B.Sc. in Computer Science or equivalent experience
  • Contributions to open-source data projects
  • Conference talks, blog posts, or other public technical writing
  • Experience running Spark on GPU with RAPIDS or using other query acceleration techniques
  • Experience with stream processing
  • Experience with dbt and/or Airflow
  • Knowledge of Ansible, Puppet, or similar configuration systems
  • Experience leveraging AI agents to accelerate engineering work
  • Familiarity with ML training pipelines and their data requirements

What the Team is Saying

Victor
Adam
Daniela
Esra
Ari
Ceci
Tanya
Giulliana
Sam
Alessandro
Jessica
Sarahjean (SJ)
Yannis
Melissa
Gili
Max
Chanan
Ceci
Jonathan
Sara
Max
Daryia
Eldad
Imola
Andrew
Dayana
Isabela
David
Fernando
Minna
Malika
Isabel

Taboola Compensation & Benefits Highlights

  • Parental & Family Support — Parental leave is often portrayed as a standout, with extended fully paid leave for primary caregivers and tenure-based leave for secondary caregivers. Return-to-work flexibility and broader family-support offerings are also emphasized.
  • Leave & Time Off Breadth — Time off is considered broad, including flexible or unlimited PTO in many U.S. locations and favorable perceptions of vacation policies. Hybrid work norms are frequently highlighted alongside generous time-off practices.
  • Healthcare Strength — Health coverage is described as comprehensive, with multiple medical plan options (including PPOs and an HDHP with HSA contributions) plus mental-health and EAP resources. Observations also note dental and vision coverage together with wellness initiatives.

Taboola Insights

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The Company
HQ: New York, NY
1,900 Employees
Year Founded: 2006

What We Do

Taboola empowers businesses to grow through performance advertising technology that goes beyond search and social and delivers measurable outcomes at scale. Taboola works with thousands of businesses who advertise directly on Realize, Taboola’s powerful ad platform, reaching approximately 600M daily active users across some of the best publishers in the world. Publishers like NBC News, Yahoo, and OEMs such as Samsung, Xiaomi and others use Taboola’s technology to grow audience and revenue, enabling Realize to offer unique data, specialized algorithms, and unmatched scale.

Why Work With Us

What sets Taboola apart? Our culture. We combine the massive data scale of a global ad-tech powerhouse with a culture anchored in empathy, non-linear growth, and trust-first flexibility. If you're looking to tackle complex AI challenges alongside brilliant, supportive peers—while being valued as a whole human being—your next chapter starts here.

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Taboola Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

Taboola offers flexibility and the ability to work remotely two days a week with three days in-office.

Typical time on-site: 3 days a week
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