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Senior Data Product Manager

Payoneer·Herzliya, ישראל·en
היברידימשרה מלאהניהול מוצרFinancial Services

Own and evolve foundational data products and platform capabilities used across the company. Set product strategy, shape scalable solutions with engineering teams, and help ensure data foundations are reliable, easy to use, and ready for evolving business and AI needs.

תחומי אחריות

  • Own product vision, strategy, and roadmap across data domains
  • Partner with product, R&D, and engineering teams during discovery and design to anticipate data needs
  • Shape scalable, reusable solutions while balancing business requirements, architecture, performance, and cost
  • Explore data, investigate issues, validate business logic, and inform product decisions
  • Improve self-service and data consumer experience
  • Define data products that are AI-ready, with clear business definitions, quality expectations, documentation, and managed dependencies
  • Lead initiatives from requirements and build-versus-buy evaluation through delivery and adoption
  • Measure product value through adoption, usability, efficiency gains, and impact of shared capabilities

דרישות

  • At least 5 years in data product management or related hands-on data roles, with ownership of complex data or technical products
  • Strong understanding of modern data architecture, data modeling, data pipelines, and cloud data platforms
  • Strong SQL and analytical skills, including hands-on data exploration, profiling, and validation
  • Product mindset and business acumen, with the ability to turn shared needs into reusable capabilities
  • Ability to participate in technical and architectural discussions and collaborate with engineering teams
  • Experience leading cross-functional initiatives, aligning stakeholders, and independently driving delivery
  • Excellent communication skills and strong English proficiency

יתרון

  • Experience with shared data products, data platforms, or developer-facing infrastructure
  • Familiarity with BigQuery, data transformation or orchestration tools, data governance, metadata, or observability
  • Experience supporting AI applications or modernizing legacy data platforms

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