PR&D Data Analyst (FinOps & Analytics)

About the role

AppsFlyer, a mobile attribution and marketing analytics company, has a PR&D Analytics & FinOps team that helps product and R&D leadership make data-driven decisions. The PR&D Data Analyst is the technical backbone of the team: owning the engineering side of data pipelines end to end, building the infrastructure and automation that lets FinOps and product/R&D analytics run on AI.

Key responsibilities

• 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 are reliable, well-structured and performant.
• Design and build automations that turn existing FinOps and product/R&D analytics processes 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 failures or inefficiencies.
• Work closely with analysts on both tracks to understand their data needs and turn them into robust solutions.

Required profile

• 3-5 years of experience in data engineering, analytics engineering or a similar hands-on technical data role.
• Degree in Industrial Engineering or a similar field.
• Independent, able to handle multiple technical priorities across domains at once.
• All-in approach with a strong sense of ownership and accountability.
• Good communication skills, able to work cross-functionally with FinOps and product/R&D analysts.

Required skills

• Excellent SQL skills.
• Hands-on experience building and maintaining data pipelines (e.g. Airflow, dbt or similar).
• Experience with BI/visualization tools such as Looker or Tableau.
• Hands-on experience with AI tools (e.g. Claude Code, Cursor, Codex) and building data structures consumable by AI.

Bonus points: automation tools such as Make, Python or other programming languages, and experience building AI agent-based workflows.