Data Analyst

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