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Product Data Analyst

AppsFlyer

Herzliya, Tel Aviv District, IsraelOn Site

Original Job Summary

Overview

AppsFlyer is seeking a talented Product Data Analyst with a pioneering spirit to join the Core Product Analysts Team. This role is central to shaping our essential product offerings by providing deep analytical insights and supporting data-informed decision-making.

What You’ll Do

  • Analyze large-scale datasets to identify trends and opportunities.
  • Develop and execute analyses to support product strategy and design.
  • Create and maintain dashboards, monitoring tools, and ETL processes.
  • Propose and lead data-driven initiatives for product improvement.

What You Have

  • 3-5 years experience as a Data Analyst, preferably in big data or SaaS.
  • Proficiency with BI tools such as Looker, PowerBI, or Tableau.
  • Bachelor’s degree in a technical or analytical field.
  • Strong proficiency in SQL and large-scale dataset handling.
  • A proactive attitude and passion for problem-solving.

Bonus Points

  • Experience with cloud data services (Amazon AWS, Google BigQuery).
  • Strong understanding of data pipelines and ETL processes.
  • Experience with AI or machine learning for product insights.
  • Introduction by an AppsFlyer team member.

Why Join Us?

Work with one of the largest mobile data sets, join an innovative team shaping mobile attribution, and enjoy a dynamic work environment that encourages learning and creativity. AppsFlyer is a global company with diverse multicultural perspectives and equal opportunity for all.

Key Skills/Competency

Data Analysis, SQL, BI Tools, ETL, Dashboarding, Cloud Data, SaaS, Mobile Attribution, Problem Solving, Data Visualization

How to Get Hired at AppsFlyer

🎯 Tips for Getting Hired

  • Customize your resume: Highlight analytical skills and big data experience.
  • Research AppsFlyer: Understand their products and global reach.
  • Prepare examples: Share successes with BI and SQL projects.
  • Network internally: Connect with current team members on LinkedIn.

📝 Interview Preparation Advice

Technical Preparation

Practice SQL queries on large datasets.
Review BI tool dashboard creation techniques.
Study ETL process design and optimization.
Familiarize with cloud data service configurations.

Behavioral Questions

Describe a time you solved a complex data problem.
Explain how you work with cross-functional teams.
Discuss handling pressure with tight product deadlines.
Share an example of proactive problem-solving.