We are looking for a first Senior Data Product Manager to join our Retail Intelligence team, reporting to the head of product.
Why is this role so important?
We're looking for a Senior Data Product Manager to drive the strategy, architecture, and execution of the data that power the Retail Intelligence products suite, eCommerce analytics product.
This role sits at the intersection of data infrastructure and customer value - you'll own the datasets, pipelines, and methodologies that help leading brands and retailers make confident decisions about their commerce assets.
What youll experience on this team?
Work with top talent across data, engineering and product teams.
Ship AI-powered capabilities iteratively, improving with every release.
Work with latest technology in an ever-evolving work environment
Operate with a startup mindset: move fast, think big, and build long-term value for customers.
Have direct impact on how customers make business decisions
What youll do as a Senior Data Product Manager?
Own the vision, roadmap, and delivery of the datasets that underpin Retail Intelligence, from eCommerce traffic and conversion data to product-level insights and category benchmarks.
Lead AI integration into internal processes and core features that speed customer decisions.
Define and track data quality metrics (completeness, coverage, freshness, accuracy) and establish validation, logging, and governance frameworks.
Lead modularization of data structures to enable scalability, and continuous improvement.
Stay close to customers and the market through ongoing research and interviews.
Partner with engineering, data science, design, sales, and marketing to deliver and drive adoption.
Requirements: 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, especially in companies that build or sell data products.
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: collaborate on APIs, pipelines, data quality, and edge cases.
AI fluency: understand how to embed AI into products and internal workflows (from prototyping through production evaluation).
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 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.
This position is open to all candidates.