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Day 23
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Reads like a Data Engineer role: pipelines and data infrastructure.
Build data structures that analysts and AI/LLM tools can use
Own, run and maintain all team data pipelines for reliability and speed
Automate FinOps and product/R&D analytics processes into AI workflows
Troubleshoot and optimize existing pipelines and automations
Translate analysts' data needs into robust technical solutions
Build data processes and structures that make the team's data usable and accessible for AI/LLM consumption.
Own the engineering and infrastructure of all data pipelines across the team's domains: build, run, and maintain them so they're reliable, well-structured, and performant.
Design and build automations that convert existing team processes across both, FinOps and product/R&D analytics, into AI-based workflows.
Troubleshoot and optimize existing pipelines and automations, proactively identifying points of failure or inefficiency.
Collaborate closely with analysts on both tracks to understand data needs and translate them into robust solutions.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications. We count a repost when the same title and location comes back as a new listing within 60 days of the last one coming down. Some hiring systems expire listings on a schedule, so repost rates vary by system.
Day 23
Similar jobs usually come down between day 5 and day 54.
From 10,736 similar postings that came down. Coming down is not always a hire.
3 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Hands on experience with automation tools (such as Make) - Proficiency in Python/ other programmatic languages for automation and data processing - Experience with building AI agent-based workflows
- 3-5 years of experience in data engineering, analytics engineering, or a similar hands-on technical data role - Excellent SQL skills - Strong hands-on experience building and maintaining data pipelines (e.g., Airflow, dbt, or similar orchestration/transformation tools)
- Excellent SQL skills - Strong hands-on experience building and maintaining data pipelines (e.g., Airflow, dbt, or similar orchestration/transformation tools) - Experience with BI/visualization tools (Looker, Tableau, or similar)
- Strong hands-on experience building and maintaining data pipelines (e.g., Airflow, dbt, or similar orchestration/transformation tools) - Experience with BI/visualization tools (Looker, Tableau, or similar) - Hands-on experience working with AI tools (e.g., Claude Code, Cursor, Codex, or similar) as part of a daily workflow, and building AI-consumable data structures
Complete your application on careers.appsflyer.com. The employer’s form will show what is required.
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We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
AppsFlyer is a cutting-edge technology company that specializes in mobile attribution and marketing analytics. We are known for our rapid deployment of innovative solutions, handling over 150 billion requests daily, focusing on data privacy and scalabilit
The PR&D Analytics & FinOps team helps ensure that product and R&D leadership make data-driven decisions. It supports the organization by connecting critical data aspects, allowing us to see the bigger picture, providing insights, and leading the organization in the right direction.
The PR&D Data Analyst is the technical backbone of the team- building the data infrastructure and automation that let our FinOps and product/R&D analytics processes run on AI. This role owns the engineering side of our data pipelines end to end, making sure our data is reliable, well-structured, and ready for both human and AI consumption.
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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Herzliya
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