Описание

The PR&D Analytics & FinOps team at AppsFlyer helps ensure that product and R&D leadership make data-driven decisions. This role involves building data infrastructure and automation that let FinOps and product/R&D analytics processes run on AI. The PR&D Data Analyst owns the engineering side of data pipelines end to end, making sure data is reliable, well-structured, and ready for both human and AI consumption.

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'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

Requirements

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

Nice to have

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