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Data Analyst
Reads like a Data Engineer role: pipelines and data infrastructure.
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingBuild 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
From the employer’s posting
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.
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 12, 202623 days ago
- Recorded sightings
- 13
- Last seen by us
- Nov 4, 2026
- Reposted
- once since Aug 19, 2026
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.
How this job compares
AppsFlyer is hiring
3 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Hiring is picking up
- 33% of open jobs were reposted
See how this role fits your experience
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.
- Python
- SQL
- dbt
- Looker
- Tableau
- Airflow
Where the posting names them
- 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
Your next step
Complete your application on careers.appsflyer.com. The employer’s form will show what is required.
Applying through Greenhouse
- No account needed: the form is one page, with an “Autofill my application” option that reads your resume.
- Greenhouse doesn’t read resumes over 2.5 MB, or details placed in a header, footer, text box, table or second column. The file still attaches, but a recruiter has to type you in by hand.
Already applied? Track this application
About the role
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.
US government figures for database architects
- Median yearly pay, May 2025
- $139,500
- Expected change, 2025 to 2035
- 9.4% more jobsagainst 3.5% for all jobs
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.
Job description
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.
What you’ll do
- 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.
- Serve as the technical connector between the FinOps and product/R&D analytics tracks, supporting both with shared, well-engineered data infrastructure.
- 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.
What you have
- 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)
- 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
- Degree in Industrial Engineering, or a similar field
- Independent, able to juggle multiple technical priorities across domains simultaneously
- All-in approach with high accountability, a sense of ownership, and passion
- Good communication skills - able to work cross-functionally with both FinOps and product/R&D analysts
Bonus points
- 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
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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