Senior Data Product Manager- Retail Intelligence
On-site · Tel Aviv, Tel Aviv, Israel
Job Summary
Senior Data Product Manager to own the vision, roadmap, and delivery of the datasets underpinning Retail Intelligence (eCommerce analytics). Lead AI integration into internal processes and core features to speed customer decisions. Define and track data quality metrics, establish governance, and enable scalable data structures. Stay close to customers through research and interviews; collaborate with engineering, data science, design, sales, and marketing to drive adoption. Bring 5+ years in data product management or equivalent, hands-on experience with large-scale data collection and pipelines, and a proven track record of cross-functional data initiatives. AI fluency and strong communication skills are essential; thrive in a fast-paced startup-like environment and in enterprise contexts. Education in CS/Engineering or equivalent practical experience preferred.
Required Qualifications
- 5+ years of experience in data product management or as a technical product manager in a big data environment
- Hands-on experience with large-scale data collection, classification, curation, and delivery systems
- Proven track record in leading cross-functional data initiatives involving data engineering, data science, and analytics teams
- Entrepreneurial mindset—proactive, and effective in ambiguity, moving quickly from insight to execution
- Comfortable in technical, data-heavy environments: APIs, pipelines, data quality, edge cases
- AI fluency: understand how to embed AI into products and internal workflows
- Excellent communication and stakeholder alignment across product, sales, and marketing
- Strong data-driven judgment: define metrics, analyze product/customer data, run experiments, and make clear tradeoffs
- High learning agility, adaptable in a fast-changing data and AI landscape
- Education: Technical background (CS, Engineering, or equivalent practical experience)
- Strong advantages: experience in startup environments, built data products, shipped AI features, eCommerce/marketplace domain experience
Desired Qualifications
- Experience in fast-moving startup environments or “startup within an enterprise.”
- Built data products: metrics, pipelines, data QA, and insight generation.
- Shipped AI features in product workflows: recommendations, forecasting, anomaly detection, insight generation, or AI agents.
- eCommerce/marketplace domain experience: ecosystems, digital shelf, conversion funnels, merchandising.
- Strong data-driven judgment: define metrics, analyze product/customer data, run experiments, and make clear tradeoffs.
- Excellent communication and stakeholder alignment across product, sales, and marketing.
- Education: Technical background (CS, Engineering, or equivalent practical experience)
- Experience in leading cross-functional data initiatives involving data engineering, data science, and analytics teams
- AI fluency: understand how to embed AI into products and internal workflows (from prototyping through production evaluation)
- Strong advantages: fast-moving startup environments or startup within an enterprise; shipped AI features in product workflows; built data products; eCommerce/marketplace domain experience
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