Senior Data Engineer
At a glance
Senior Data Engineering role at AppsFlyer. Herzliya.
Pay not stated Data Engineer salary
dataroles summary, based on the employer's posting.
What you'll do
- Build and refine web-event pipelines, handling ingestion, distributed processing and serving while meeting freshness and accuracy targets
- Set pipeline architecture from initial specifications to launch, document decisions and review designs across the team
- Choose where SQL or Spark fits, and work with architects on designs spanning multiple teams
- Plan work with the team lead, divide large efforts into deliverables and represent the team in technical discussions
- Take production incidents through resolution and implement fixes that prevent recurrence
What you bring
- At least six years building and operating production data or big-data systems at scale
- A computer science degree or equivalent qualification
- Strong practical Apache Spark skills, including diagnosing skew, execution, partitioning and memory issues
- Experience using a cloud analytics warehouse for both processing and serving, plus production-scale orchestration and cloud systems
- A record of taking data-system designs from documented trade-offs through production, and hands-on daily use of AI tools
Who this fits
This senior role suits an engineer ready to guide pipeline design, advise the team on Spark and data modeling, and work with the team lead on priorities. The role is based in Herzliya, Israel.
From the employer
AppsFlyer processes 150+ billion events across its platform, and our Web Attribution team is at the center of extending that power beyond mobile. We build the product that shows advertisers which campaigns really drive results on the web. We attribute every web user journey, from first click to conversion, across thousands of apps and billions of sessions.
We're looking for a Senior Data Engineer to own the technical direction of our pipelines. You'll be the team's go-to data engineering expert and a key knowledge holder: the person the team turns to for Spark, data modeling, and the hardest pipeline problems. You'll lead the team's design work and work closely with the team lead on planning and technical priorities. You'll shape the product that advertisers and marketers rely on every day.
What you’ll do
- Build & Own End-to-End Pipelines: Build and improve pipelines that process billions of web events (sessions, in-app events, conversions) with strict freshness and accuracy SLAs, from ingestion through distributed processing to the serving layer.
- Lead Design & Architecture: Own the technical design of the team's pipelines, from spec to production. Write design docs, review the team's designs, and make the key trade-offs, such as what runs in SQL and what runs in Spark. Work with the group's architects on cross-team designs.
- Drive Technical Planning: Work with the team lead on the roadmap, planning, and priorities. Break large projects into clear deliverables. Represent the team in technical discussions with Product, R&D, and partner teams. Own production incidents end-to-end and turn them into lasting fixes.
What you have
- 6+ years in Data / Big Data Engineering, including building and running production systems at scale.
- B.Sc. in Computer Science or equivalent.
- Deep, hands-on Apache Spark experience: you understand execution plans, partitioning, and memory management, and you know how to debug skew and performance problems at scale.
- Deep experience with a cloud analytical warehouse (BigQuery, Snowflake, Redshift, or Databricks SQL) as both a processing and serving layer. BigQuery is a strong advantage.
- A proven track record in data-system design: you've written design docs, made trade-offs between cost, latency, and correctness, and taken designs all the way to production.
- Experience with workflow orchestration (e.g., Airflow) and cloud environments at production scale. GCP preferred.
- Strong programming fundamentals: clean, testable, production-grade code. Scala preferred; Python for orchestration.
- A natural instinct for data quality: you think about edge cases, dedup logic, and "what happens when this field is null" before anyone asks.
- Hands-on use of AI tools in your daily engineering work, and a clear view of where AI helps data engineering and where it doesn't.
Bonus points
- Experience building or maintaining attribution / AdTech data systems.
- Advanced Scala or functional programming experience.
- Experience with attribution models (last-click, multi-touch, view-through).
- Experience with SQL-based transformation frameworks (Dataform, dbt) or data-mesh / data-product platforms.
- Experience with Kafka or streaming systems.
- Experience running LLMs or ML pipelines in production.
- Being introduced by an AppsFlyer team member
As a global company operating from 25 offices across 19 countries, we reflect the human mosaic of the diverse and multicultural world in which we live. We ensure equal opportunities for all of our employees and promote the recruitment of diverse talents to our global teams without consideration of race, gender, culture, or sexual orientation. We value and encourage curiosity, diversity, and innovation from all our employees, customers, and partners.
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