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.
- 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
- 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.
“As a Customer Obsessed company, we must first be Employee Obsessed. We need to make sure that we provide the team with the tools and resources they need to go All-In.” Oren Kaniel, CEO
Skills Required
- 3-5 years of experience in data engineering, analytics engineering, or a similar hands-on technical data role
- Excellent SQL skills
- Hands-on experience building and maintaining data pipelines using tools such as Airflow, dbt, or similar
- Experience with BI and visualization tools such as Looker, Tableau, or similar
- Hands-on experience using AI tools such as Claude Code, Cursor, Codex, or similar in daily workflows
- Experience building AI-consumable data structures
- Degree in Industrial Engineering or a similar field
- Ability to work independently and manage multiple technical priorities
- Strong accountability, ownership, and passion
- Good cross-functional communication skills
- Hands-on experience with automation tools such as Make
- Proficiency in Python or other programming languages for automation and data processing
- Experience building AI agent-based workflows
AppsFlyer Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about AppsFlyer and has not been reviewed or approved by AppsFlyer.
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Wellbeing & Lifestyle Benefits — Wellbeing support is positioned as a meaningful part of the rewards package, including private health insurance and wellness offerings like fitness classes. Additional extras such as events, work‑from‑home support, and global mobility opportunities are portrayed as adding tangible value beyond cash compensation.
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Equity Value & Accessibility — Equity is framed as broadly accessible, with stock options described as available to all employees. This expands the total rewards mix and can make overall compensation feel stronger even when salary alone is debated.
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Strong & Reliable Incentives — Total compensation in certain technical and revenue roles is presented as capable of reaching competitive levels, implying meaningful upside where role/market fit is strong. Sales compensation is described as potentially attractive on-target, which can reinforce perceived earning opportunity when performance aligns with plan design.
AppsFlyer Insights
What We Do
AppsFlyer helps brands make good choices for their business and their customers through innovative, privacy-preserving measurement, analytics, fraud protection, and engagement technologies. Built on the idea that brands can increase customer privacy while providing exceptional experiences, AppsFlyer empowers thousands of creators and 8,000+ technology partners to create better, more meaningful customer relationships. To learn more, visit www.appsflyer.com.
